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At least 1,243 records · Page 69

Adaptive identification for the dynamics of large space structures

A new approach for identifying the dynamics of large space structures using noisy measurements is presented. In this approach, a modal system description is avoided and, hence, the a priori specification of model order. Instead, the system's order is recursively determined on-line, along with its parameters, using recursive lattice filters which are widely used in adaptive signal processing. The order determination is carried out based on statistical hypothesis testing theory. The approach is illustrated for the problem of identifying the structural dynamic characteristics of a free-free beam. Results on the effectiveness and accuracy of the identification scheme with respect to noise levels, sampling rates, and data window sizes are presented

Sundararajan, N.↗

Deep Learning Explicit Differentiable Predictive Control Laws for Buildings

We present a differentiable predictive control (DPC) methodology for learning constrained control laws for unknown nonlinear systems. DPC poses an approximate solution to multiparametric programming problems emerging from explicit nonlinear model predictive control (MPC). Contrary to approximate MPC, DPC does not require supervision by an expert controller. Instead, a system dynamics model is learned from a small dataset of recorded observations of the perturbed system's dynamics and the control law is optimized offline by interaction with the learned system model. The DPC method is based on two sequential steps, i) system identification using a constrained neural state-space model, and ii) optimization of an explicit control law parametrized by another neural network in closed-loop simulation with the identified neural state-space model. The combination of a differentiable closed-loop system and penalty methods for constraint handling of system outputs and inputs allows us to optimize the control law's parameters directly by backpropagating economic MPC loss through the learned system model. By incorporating domain knowledge and leveraging established techniques from optimal control, our method leverages deep neural networks as nonlinear function approximators for system identification and control while avoiding concomitant costs of intractably large datasets, and computationally expensive over-parametrized models. The scalability, data efficiency, and constrained optimal control capability of the proposed DPC method are demonstrated in simulation using a multi-zone building emulator.

Drgona, Jan↗

Nuclear Data Sheets for A=100

Here, evaluated experimental data are presented for 15 known nuclides of mass 100 (Kr, Rb, Sr, Y, Zr, Nb, Mo, Tc, Ru, Rh, Pd, Ag, Cd, In, Sn). Recommended values are given for level parameters, γ and β radiations, and other spectroscopic information. No excited states are known in 100 Rb and 100 Sn. Except for isotopic identification, no information is available for the decay of the 100 Kr isotope, and limited information is known about the decay properties of the 100 Sn isotope. According to Fig. 2 (A/Q versus counts plot) and as mentioned in the text in 2021Su01, 100 Br isotope was not observed, although, discovery of 101 Br was claimed in this work. In the case of 100 Pd, the agreement in the orderings of the γ-ray cascades and γ-ray inventory between various studies of high-spin structures remains poor at high excitation energies (>9 MeV). For 100 Y, the assignments of the two previously known half-lives to the respective states (g.s. and the 145-keV isomer) remain to be established. Here, this work supersedes earlier full evaluations of A=100 by 2008Si01, 1997Si09, 1990Si05 and 1974Ko37.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Machine-learning-accelerated multimodal characterization and multiobjective design optimization of natural porous materials

Natural porous materials such as nanoporous clays are used as green and low-cost adsorbents and catalysts. The key factors determining their performance in these applications are the pore morphology and surface activity, which are typically represented by properties such as specific surface area, pore volume, micropore content and pH. The latter may be modified and tuned to specific applications through material processing and/or chemical treatment. Characterization of the material, raw or processed, is typically performed experimentally, which can become costly especially in the context of tuning of the properties towards specific application requirements and needing numerous experiments. In this work, we present an application of tree-based machine learning methods trained on experimental datasets to accelerate the characterization of natural porous materials. The resulting models allow reliable prediction of the outcomes of experimental characterization of processed materials (R2 from 0.78 to 0.99) as well as identification of key factors contributing to those properties through feature importance analysis. Furthermore, the high throughput of the models enables exploration of processing parameter–property correlations and multiobjective optimization of prototype materials towards specific applications. We have applied these methodologies to pinpoint and rationalize optimal processing conditions for clays exploitable in acid catalysis. One of such identified materials was synthesized and tested revealing appreciable acid character improvement with respect to the pristine material. Specifically, it achieved 79% removal of chlorophyll-a in acid catalyzed degradation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Single-shot ionization-based monitor for pulsed electron beams

In this work, we present an experimental demonstration of a single-shot, nondestructive electron beam diagnostic based on the ionization of a low-density pulsed gas jet. In our study, 7 MeV electron bunches from a radio-frequency photoinjector, carrying up to 100 pC of charge, traversed a localized distribution of nitrogen gas (N 2 ). The interaction of the electron bunches with the N 2 gas generated a correlated signature in the ionized particle distribution, which was spatially magnified using a series of electrostatic lenses and recorded with a microchannel-plate detector. Various modalities, including point-to-point imaging and velocity mapping, are investigated. A temporal trace of the detector current enabled the identification of single- and double-ionization events. The characteristics of the ionization distribution, dependence on gas density, total bunch charge, and other parameters, are described. Approaches to scaling to higher electron bunch density and energy are suggested. Additionally, the instrument proves useful for comprehensive studies of the ionization process itself.

47 OTHER INSTRUMENTATION↗

Baby-MIND neutrino detector

The main objective of the Baby-MIND detector (Magnetized Iron Neutrino Detector) is the study of muon charge identification efficiency for muon momenta from 0.3 to 5 GeV/ c. This paper presents the results of measurement of the Baby-MIND parameters.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Repairing polycrystalline IN 100 using additive manufacturing (CRADA NFE-17-06791 Final Report)

The overall goal of this Manufacturing Demonstration Facility (MDF) technical collaboration project is to extend the use of the laser blown powder additive manufacturing process to enable the repair of polycrystalline high γ' Ni base super alloys, and to qualify the repaired parts for end use. The goal of phase 1 of this project was to evaluate the cracking susceptibility of Inconel 100 samples, and to identify parameters that would yield crack free repair deposits on representative geometries using a surrogate material as a substrate. A detailed design of experiments was performed in conjunction with thermomechanical modeling to determine processing conditions. A set of process parameters were identified which yielded minimal cracking. Further modeling was used to identify the preheat condition necessary to obtain crack free deposits. Following identification of the preheat, a furnace was integrated within the chamber of the blown powder Direct Energy Deposition (DED) system, and deposits were fabricated with on a preheated furnace. The results show that crack free deposits with dimensions 35x15x0.5 mm 3 can be fabricated. With this success obtained in phase 1 the goal of phase 2, if awarded, would be to fabricate the deposit on the actual IN 100 substrates develop heat treatment procedures and qualify the repair procedures.

36 MATERIALS SCIENCE↗

Direct measurements of plasma characteristics in space-simulation beam-plasma interactions

Recent laboratory investigations of space-simulated electron-beam-plasma interactions are discussed. The plasma has been characterized with respect to its spatial distributions in density, temperature, and density fluctuation power spectra. The latter results have been further classified in terms of amplitude and spectral distributions. The overall results include: (1) detailed radial profiles of plasma density as a function of beam parameters; (2) the association of low-frequency large amplitude fluctuations with ion acoustic, ion cyclotron, and drift-wave modes; (3) the identification and spatial mapping of suprathermal electrons in the beam core; and (4) the experimental definition of a density-dependent criterion for the ignition of the beam-plasma-discharge.

Szuszczewicz, E. P.↗

Simulation Aspects in the Study of Rectification of Satellite Scanner Data

Complete sensor/platform modelling is derived and used for the generation of synthetic data and for rectification studies of satellite scanner data. All satellite position and sensor attitude parameters are recovered. Rectification accuracy improves marginally when using more than 25 control points, and is highly sensitive to errors in image point identification.

Mikhail, E. M.↗

On-orbit systems identification of flexible spacecraft

The process of on-orbit systems identification of flexible spacecraft is examined in terms of the difficulties that are expected because of the potentially unmanageable number of unknown model parameters due to the very high order system models involved. A Jordon block canonical form and global model parameters are used to reduce the number of unknown parameters to manageable numbers. A Bayesian approach is discussed which enables the merging of theoretical models with ground or on-orbit test results by using Unconditional Maximum Likelihood Parameter Estimation. A Modified Newton-Raphson technique is proposed for determining the model parameter estimates and an expected fit error criterion is recommended for the determination of the model structure and order reduction.

Taylor, L. W., Jr.↗

1987 overview of free-piston Stirling technology for space power application

The Lewis Research Center program concerned with the development of a free-piston Stirling engine for space-power applications is examined. The system mass of a Stirling system is compared to that of a Brayton system for the same peak temperature and output power; the advantages of the Stirling system are discussed. The predicted and experimental performances of the 25 kWe opposed-piston space power demonstrator engine are evaluated. It is determined that in order to enhance performance the regenerator needs to be modified, and the gas bearing flow between the displacer and power piston needs to be isolated in order to increase the operating stroke. Identification and correction of the energy losses, the design and operation of the linear alternator, and heat exchange concepts are considered. The design parameters and conceptual design characteristics for a 25 kWe single-cylinder free-piston Stirling space-power converter are described.

Slaby, Jack G.↗

An empirical investigation of the InP shallow-homojunction solar cell

An experimental study of the performance of epitaxially grown InP shallow-homojunction solar cells as a function of the thickness and carrier concentration in the base and emitter layers is presented. Identification of improvements to cell design leading to higher performance is emphasized. As a result, using a near-optimum set of design parameters, cells with conversion efficiencies of 20.3 percent (global) and 17.6 percent (AM0) have been achieved. For such cells, it is shown that the internal response of the base layer is essentially perfect, whereas the emitter-layer properties can be improved substantially and warrant further investigation. Discrepancies between the results of the present study and those of earlier modeling efforts are discussed.

Wanlass, M. W.↗

A search for the rotational transitions of H2D+ at 1370 GHz and H3O+ at 985 GHz

A search was made for the 1370 GHz lowest rotational transition of the molecular ion H2D+ in NGC 2264, W3, and the IRc2 region of M42. No emission lines were seen, but an absorption feature was detected toward IRc2. The column density and fractional abundance were calculated using a tentative identification of the line as the transition of para H2D+. The LSR velocity and the measured line width are consistent with the dynamical parameters of the hot core source. Physical parameters deduced from the data differ from those derived from millimeter-wave observations of the hot core condensation. It is suggested that significant amounts of low-density gas are associated with this region and that the material is cold enough for enhanced deuterium fractionation to occur. A search was also made for the 985 GHz transition of ortho H3O+ in W3 and IRc2 with negative results.

Boreiko, R. T.↗

F-15B Quiet Spike(TradeMark) Aeroservoelastic Flight-Test Data Analysis

System identification is utilized in the aerospace community for development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlin ear systems. In this report, we show the application of one such nonlinear system identification technique, structure detection, for the an alysis of Quiet Spike(TradeMark)(Gulfstream Aerospace Corporation, Savannah, Georgia) aeroservoelastic flight-test data. Structure detectio n is concerned with the selection of a subset of candidate terms that best describe the observed output. Structure computation as a tool fo r black-box modeling may be of critical importance for the development of robust, parsimonious models for the flight-test community. The ob jectives of this study are to demonstrate via analysis of Quiet Spike(TradeMark) aeroservoelastic flight-test data for several flight conditions that: linear models are inefficient for modelling aeroservoelast ic data, nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data an d the model structure and parameters vary as the flight condition is altered.

Kukreja, Sunil L.↗

F-15B QuietSpike(TradeMark) Aeroservoelastic Flight Test Data Analysis

System identification or mathematical modelling is utilised in the aerospace community for the development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. The reason for utilising a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance for the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data for several flight conditions (Mach number) that (i) linear models are inefficient for modelling aeroservoelastic data, (ii) nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data and (iii) the model structure and parameters vary as the flight condition is altered.

Kukreja, Sunil L.↗

Structure Computation of Quiet Spike[Trademark] Flight-Test Data During Envelope Expansion

System identification or mathematical modeling is used in the aerospace community for development of simulation models for robust control law design. These models are often described as linear time-invariant processes. Nevertheless, it is well known that the underlying process is often nonlinear. The reason for using a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades, the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B Quiet Spike(TradeMark) aeroservoelastic flight-test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description that may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance for the development of robust parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion, which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B Quiet Spike aeroservoelastic flight-test data for several flight conditions that 1) linear models are inefficient for modeling aeroservoelastic data, 2) nonlinear identification provides a parsimonious model description while providing a high percent fit for cross-validated data, and 3) the model structure and parameters vary as the flight condition is altered.

Kukreja, Sunil L.↗

On the Development of Parameterized Linear Analytical Longitudinal Airship Models

In order to explore Titan, a moon of Saturn, airships must be able to traverse the atmosphere autonomously. To achieve this, an accurate model and accurate control of the vehicle must be developed so that it is understood how the airship will react to specific sets of control inputs. This paper explains how longitudinal aircraft stability derivatives can be used with airship parameters to create a linear model of the airship solely by combining geometric and aerodynamic airship data. This method does not require system identification of the vehicle. All of the required data can be derived from computational fluid dynamics and wind tunnel testing. This alternate method of developing dynamic airship models will reduce time and cost. Results are compared to other stable airship dynamic models to validate the methods. Future work will address a lateral airship model using the same methods.

aerobot↗

Validation Study in SAS4A Code in Simulated Mild TOP Condition

Model improvements and validation efforts for SAS4A code, which is the most advanced computer code for simulating the the primary phase of the Core Disruptive Accident (CDA) of MOX-fueled Sodium-cooled Fast Reactors, have been performed utilizing the experimental data from the CABRI programs by JAEA (Japan Atomic Energy Agency), IRSN (Institut de Radioprotection et de Surete Nucleaire), CEA (Commissariat a l'Energie Atomique et aux Energies Alternatives) and KIT (Karlsruhe Institute of Technology). In order to confirm validity of improved models of SAS4A, a systematic and comprehensive validation plan was defined. It was based on the PIRT (Phenomena Identification and Ranking Table) result for CDA of MOX-fueled fast reactors. The fuel failure position and time are the most important parameters, which dominate the analytical results in a reactor calculation. The failure position will affect the reactivity feedback due to the fuel distribution after failure and consequently would have an effect on the energy release in the initiating phase. This paper describes the preliminary result of validation study for SAS4A code in simulated Transient Over-Power (TOP) condition. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗