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At least 469 records · Page 26

Determining Aircraft Moments of Inertia from Flight Test Data

Flight test maneuvers and dynamic modeling techniques were developed for determining aircraft moments of inertia from flight test data. Full nonlinear rigid-body rotational equations of motion were used in the analysis, with aerodynamic moment dependencies modeled by linear expansions in the aircraft states and controls. Aerodynamic parameters were estimated simultaneously with inertia parameters using equation-error modeling applied to flight test data from maneuvers designed specifically for this problem. The approach was demonstrated using a nonlinear F 16 simulation, then applied to a remotely-piloted subscale aircraft flight test. Errors in the aircraft moment of inertia parameters determined from simulated F-16 flight test data were less than 6 percent compared to the true values in the simulation. Flight test results for the subscale aircraft were within 6 percent of ground-test values obtained using the same aircraft.

Parameter estimation↗

Observer-Based Nonlinear Control Scheme to Reduce Oscillations and Zero Crossing in Skid-Steer Vehicles

Motion sickness is a common condition experienced by drivers of skid-steer vehicles, primarily caused by zero crossing and oscillations in undamped systems. This study proposes an observer-based nonlinear control scheme to reduce transient oscillations and zero-crossing phenomena in skid-steer vehicles, thereby potentially alleviating motion sickness. Reducing transient oscillations and zero crossing in the transient response may alleviate motion sickness. A nonlinear damping controller is designed to improve transient response by reducing oscillations and zero-crossing. To design the controller, a reduced-order kinematic model based on coordinate transformation is developed. This transformation not only converts the system modeling into a controllable form but also enhances control performance. Modeling error is addressed by considering the distance between the center of the vehicle and the sensor location. Despite these improvements, model uncertainties and external disturbances remain, which may degrade control performance. To ensure robustness and estimate such disturbances, a high-order sliding mode observer (HOSMO) is incorporated. The effectiveness of the proposed method is validated through MATLAB/Simulink and TruckMaker simulations. From the simulation results, it was shown that the proposed method reduced the mean squared error of the tracking error to within 10 % compared to the state feedback controller with the HOSMO.

Seo, Jiwon [Chung-Ang University, Seoul (Korea, Re↗

Using Modern Design Tools for Digital Avionics Development

Using Modem Design Tools for Digital Avionics Development Shrinking development time and increased complexity of new avionics forces the designer to use modem tools and methods during hardware development. Engineers at the Marshall Space Flight Center have successfully upgraded their design flow and used it to develop a Mongoose V based radiation tolerant processor board for the International Space Station's Water Recovery System. The design flow, based on hardware description languages, simulation, synthesis, hardware models, and full functional software model libraries, allowed designers to fully simulate the processor board from reset, through initialization before any boards were built. The fidelity of a digital simulation is limited to the accuracy of the models used and how realistically the designer drives the circuit's inputs during simulation. By using the actual silicon during simulation, device modeling errors are reduced. Numerous design flaws were discovered early in the design phase when they could be easily fixed. The use of hardware models and actual MIPS software loaded into full functional memory models also provided checkout of the software development environment. This paper will describe the design flow used to develop the processor board and give examples of errors that were found using the tools. An overview of the processor board firmware will also be covered.

Hyde, David W.↗

A Differentiable Hydrology Approach for Modeling With Time-Varying Parameters

In the analysis of observational data with mathematical models, it is often desirable to let one or more model parameters vary with time to account for changing environmental conditions or to offer more flexibility. A standard approach for dynamic models is to allow for the number of parameters to grow as a function of time, leading to a high-dimensional inference problem for long data records. We propose using Hamiltonian Monte Carlo, a gradient-based Markov chain Monte Carlo (MCMC) method, to perform Bayesian inference for time-varying parameters (TVP) in hydrology models. As derivatives of model error functions with regard to parameters are not available in closed form, we implemented the GR4J rainfall-runoff models in Theano/PyMC3, and Jax/NumPyro, allowing for the application of automatic differentiation techniques. A simulation experiment assessing the viability of these methods for recovering underlying temporal variation in parameters indicates that a discrete Gaussian random walk-based prior appears to be best suited across a range of scenarios while the continuous-time Gaussian process compares relatively poorly. In an analysis of 20 years of daily real-world streamflow records from the Model Parameter Estimation Experiment (MOPEX) hydrology data set with increasing data sparsity and at multiple temporal resolutions, we find that TVP inference with gradient-based MCMC is a flexible and reliable approach for analyzing hydrology models with dynamic parameter sets.

54 ENVIRONMENTAL SCIENCES↗

Coherent manipulation of graph states composed of finite-energy Gottesman-Kitaev-Preskill-encoded qubits

Graph states are a central resource in measurement-based quantum information processing. In the photonic qubit architecture based on Gottesman-Kitaev-Preskill (GKP) encoding, the generation of high-fidelity graph states composed of realistic, finite-energy approximate GKP-encoded qubits thus constitutes a key task. We consider the finite-energy approximation of GKP-qubit states given by a coherent superposition of shifted finite-squeezed vacuum states, where the displacements are Gaussian distributed. We present an exact description of graph states composed of such approximate GKP qubits as a coherent superposition of a Gaussian ensemble of randomly displaced ideal GKP-qubit graph states. Using standard Gaussian dynamics, we track the transformation of the covariance matrix and the mean-displacement vector elements of the Gaussian distribution of the ensemble under tools such as GKP-Steane error-correction and fusion operations that can be used to grow large high-fidelity GKP-qubit graph states. The covariance matrix elements capture the noise in the graph state due to the finite-energy approximation of GKP qubits, while the mean displacements relate to the possible absolute shift errors on the individual qubits arising conditionally from the homodyne measurements that are a part of these tools. Our work thus pins down an exact coherent error model for graph states generated from truly finite-energy GKP qubits, which can shed light on their error-correction properties.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Towards Smart Grids Enhanced Situation Awareness: A Bi-Level Quasi-Static State Estimation Model

Smart Grid situational awareness is provided by Energy Management Systems. A core process of these systems is State Estimation. The great majority of state estimators model the Smart Grid through a set of nonlinear algebraic equations, named the measurement model. Problem formulation considers the Gauss solution. Several model improvements have been presented regarding the Gauss solution, aiming between others to provide measurement noise robustness to the state estimation process. While considerable effort has been focused on such developments, state estimation is still constrained by the implicit modelling error, and thus inevitably vulnerable to cyber-threats. In this work, a state estimation bi-level formal model is presented towards Smart Grids enhanced situational awareness considering the concepts of synthetic measurements and innovation. Comparative test results with the state-of-the-art on the IEEE 14-bus system are presented highlighting improved situational awareness to bad data. Easy-to-implement model, without hard-to-derive parameters, built-on the classic weighted least squares solution, highlight potential aspects for real-life implementation.

cyber security↗

Study of automatic flare and decrab guidance and control system for the space shuttle

The automatic landing of an unpowered space shuttle vehicle was studied along with the design of the guidance and flight controls, selection of the ground reference component of the landing system (signals in space), and evaluation of the performance of the overall system. The study was carried out by means of an all-digital simulation which incorporated wind shears, gusts and error models for the hardware components. The performance of the landing system operating in winds and turbulence and with hardware errors was determined by Monte Carlo techniques. It was found that the interactions of turbulence and vehicle characteristics were the limiting factors on system performance. The touchdown errors due to the measurement errors of the ground reference system were less significant. The guidance designed was predictive in the longitudinal direction and fixed path in the lateral direction.

Cockayne, W.↗

Experimental Robust Control Studies on an Unstable Magnetic Suspension System

This study is an experimental investigation of the robustness of various controllers designed for the Large Angle Magnetic Suspension Test Fixture (LAMSTF). Both analytical and identified nominal models are used for designing controllers along with two different types of uncertainty models. Robustness refers to maintain- ing tracking performance under analytical model errors and dynamically induced eddy currents, while external disturbances are not considered. Results show that incorporating robustness into analytical models gives significantly better results. However, incorporating incorrect uncertainty models may lead to poorer performance than not designing for robustness at all. Designing controllers based on accurate identified models gave the best performance. In fact, incorporating a significant level of robustness into an accurate nominal model resulted in reduced performance. This paper discusses an assortment of experimental results in a consistent manner using robust control theory.

Lim, Kyong B.↗

Quantum-classical embedding via ghost Gutzwiller approximation for enhanced simulations of correlated electron systems

Simulating correlated materials on present-day quantum hardware remains challenging due to limited quantum resources. Quantum embedding methods offer a promising route by reducing computational complexity through the mapping of bulk systems onto effective impurity models, allowing more feasible simulations on pre- and early-fault-tolerant quantum devices. Here, this work develops a quantum-classical embedding framework based on the ghost Gutzwiller approximation to enable quantum-enhanced simulations of ground-state properties and spectral functions of correlated electron systems. Circuit complexity is analyzed using an adaptive variational quantum algorithm on a statevector simulator, applied to the infinite-dimensional Hubbard model with increasing ghost mode numbers from 3 to 5, resulting in circuit depths growing from 16 to 104. Noise effects are examined using a realistic error model, revealing significant impact on the spectral weight of the Hubbard bands. To mitigate these effects, the Iceberg quantum error detection code is employed, achieving up to 40% error reduction in simulations. Finally, the accuracy of the density matrix estimation and the derived spectral function is benchmarked on IBM and Quantinuum quantum hardware, featuring distinct qubit-connectivity and employing multiple levels of error mitigation techniques.

Chen, I-Chi [Ames Laboratory (AMES), Ames, IA (Uni↗

To Err is Normable: The Computation of Frequency-Domain Error Bounds from Time-Domain Data

This paper exploits the relationships among the time-domain and frequency-domain system norms to derive information useful for modeling and control design, given only the system step response data. A discussion of system and signal norms is included. The proposed procedures involve only simple numerical operations, such as the discrete approximation of derivatives and integrals, and the calculation of matrix singular values. The resulting frequency-domain and Hankel-operator norm approximations may be used to evaluate the accuracy of a given model, and to determine model corrections to decrease the modeling errors.

Hartley, Tom T.↗

Simulations of Cyclone Sidr in the Bay of Bengal with a High-Resolution Model: Sensitivity to Large-Scale Boundary Forcing

The predictability of Cyclone Sidr in the Bay of Bengal was explored in terms of track and intensity using the Advanced Research Hurricane Weather Research Forecast (AHW) model. This constitutes the first application of the AHW over an area that lies outside the region of the North Atlantic for which this model was developed and tested. Several experiments were conducted to understand the possible contributing factors that affected Sidr s intensity and track simulation by varying the initial start time and domain size. Results show that Sidr s track was strongly controlled by the synoptic flow at the 500-hPa level, seen especially due to the strong mid-latitude westerly over north-central India. A 96-h forecast produced westerly winds over north-central India at the 500-hPa level that were notably weaker; this likely caused the modeled cyclone track to drift from the observed actual track. Reducing the model domain size reduced model error in the synoptic-scale winds at 500 hPa and produced an improved cyclone track. Specifically, the cyclone track appeared to be sensitive to the upstream synoptic flow, and was, therefore, sensitive to the location of the western boundary of the domain. However, cyclone intensity remained largely unaffected by this synoptic wind error at the 500-hPa level. Comparison of the high resolution, moving nested domain with a single coarser resolution domain showed little difference in tracks, but resulted in significantly different intensities. Experiments on the domain size with regard to the total precipitation simulated by the model showed that precipitation patterns and 10-m surface winds were also different. This was mainly due to the mid-latitude westerly flow across the west side of the model domain. The analysis also suggested that the total precipitation pattern and track was unchanged when the domain was extended toward the east, north, and south. Furthermore, this highlights our conclusion that Sidr was influenced from the west side of the domain. The displacement error was significantly reduced after the domain size from the western model boundary was decreased. Study results demonstrate the capability and need of a high-resolution mesoscale modeling framework for simulating the complex interactions that contribute to the formation of tropical cyclones over the Bay of Bengal region

Kumar, Anil↗

Comparison between the land surface response of the ECMWF model and the FIFE-1987 data

An averaged time series for the surface data for the 15 x 15 km FIFE site was prepared for the summer of 1987. Comparisons with 48-hr forecasts from the ECMWF model for extended periods in July, August, and October 1987 identified model errors in the incoming SW radiation in clear skies, the ground heat flux, the formulation of surface evaporation, the soil-moisture model, and the entrainment at boundary-layer top. The model clear-sky SW flux is too high at the surface by 5-10 percent. The ground heat flux is too large by a factor of 2 to 3 because of the large thermal capacity of the first soil layer (which is 7 cm thick), and a time truncation error. The surface evaporation was near zero in October 1987, rather than of order 70 W/sq m at noon. The surface evaporation falls too rapidly after rainfall, with a time-scale of a few days rather than the 7-10 d (or more) of the observations. On time-scales of more than a few days the specified 'climate layer' soil moisture, rather than the storage of precipitation, has a large control on the evapotranspiration. The boundary-layer-top entrainment is too low. This results in a moist bias in the boundary-layer mixing ratio of order 2 g/Kg in forecasts from an experimental analysis with nearly realistic surface fluxes; this because there is insufficient downward mixing of dry air.

Betts, Alan K.↗

C-band radar pulse Doppler error: Its discovery, modeling, and elimination

The discovery of a C Band radar pulse Doppler error is discussed and use of the GEOS 3 satellite's coherent transponder to isolate the error source is described. An analysis of the pulse Doppler tracking loop is presented and a mathematical model for the error was developed. Error correction techniques were developed and are described including implementation details.

Krabill, W. B.↗

Development of simplified model for injection rate prediction of diesel injectors during transient and steady operation

Determining the injection rate of the diesel injector during the transient short injection operations is a critical matter to enhance the combustion process by improving air/fuel mixture formation. In this regard, numerous injection models have been suggested in the literature to predict the injection rate accurately. However, such algorithms have not precisely predicted the rate of injection (ROI) in transient short injection events. In addition, most of those models require many input parameters to characterize hydraulic and mechanical subsystems in the injector, which can make them inconvenient to tune for different injector specifications, in other words not suitable for universal usage. Therefore, our study aims to develop a simple injection model that can predict injection rate precisely in the short and long injection durations considering relatively fewer input parameters. The model traces the pressure variation inside the sac based on the bulk modulus theory to predict nozzle exit velocity, thus the injection rate of the injector. In the algorithm, the bulk modulus of fuel (E) and discharge coefficients of the nozzle hole and needle seat (C d,H and C d,N ) have been considered to vary rather than set constant during the injection process since such flow parameters would have a critical impact on the flow development at the transient stage, thus affecting the injection rate of diesel injectors. Here with this modelling strategy, the accuracy of the new model on ROI prediction was confirmed with acceptable model error for both short and long injection durations by validating against experimental results. To understand the effect of the new model scheme on ROI prediction, ROI results with the new model have been discussed by comparing it with the ROI results predicted with constant flow parameters.

42 ENGINEERING↗

An underestimated negative cloud feedback from cloud lifetime changes

As the atmosphere warms, part of the cloud population shifts from ice and mixed phase (“cold”) to liquid (“warm”) clouds. Because warm clouds are more reflective and longerlived, this phase change reduces the solar flux absorbed by Earth and constitutes a negative radiative feedback. This cooling feedback is weaker in CMIP6 than in CMIP5, contributing to greater greenhouse warming. While this change is often attributed to improvements in simulated cloud phase, another model bias persists: warm clouds precipitate too readily, potentially leading to underestimated negative lifetime feedbacks. In this work, we modify a climate model to better simulate warm rain probability and find it exhibits a cloud lifetime feedback nearly three times larger than the default model. This suggests model errors in cloud-precipitation processes may bias cloud feedbacks as much as CMIP5–CMIP6 climate sensitivity differences. Reliable climate model projections therefore require improved cloud process realism guided by process-oriented observations and observational constraints.

54 ENVIRONMENTAL SCIENCES↗

Black hole-neutron star binaries near neutron star disruption limit in the mass regime of event GW230529

In May 2023, the LIGO-Virgo-KAGRA (LVK) Collaboration reported the likely black hole-neutron star (BHNS) merger GW230529_181500. The signal was observed with high significance in only one detector, limiting constraints on the black hole spin and motivating our study of disruption in this mass regime. That event is expected to be the merger of a 2.5–4.5 M ⊙ primary with a secondary compact object of mass between 1.2–2.0 M ⊙ . This makes it the first BHNS merger with a significant potential for the production of electromagnetic (EM) counterparts, and provides further evidence for compact objects existing within the suspected lower mass gap. To produce post-merger EM transients, the component of the black hole spin aligned with the orbital angular momentum must be sufficiently high, allowing the neutron star to be tidally disrupted. The disrupting BHNS binary may then eject a few percent of a solar mass of matter, leading to an observable kilonova driven by radioactive decays in ejecta, and/or a compact-binary gamma-ray burst (cbGRB) resulting from the formation of an accretion disk and relativistic jet. Determining which mergers lead to disruption of the neutron star is necessary to predict the prevalence of EM signals from BHNS mergers, yet most BHNS simulations so far have been performed far from the minimum spin required for tidal disruption. Here, we use the Spectral Einstein Code to explore the behavior of BHNS mergers in a mass range consistent with GW230529_181500 close to that critical spin, and compare our results against the mass remnant model currently used by the LVK Collaboration to predict the probability of tidal disruption. Furthermore, our numerical results reveal the emergence of non-zero accretion disks even below the predicted NS disruption limit, of low mass but capable of powering cbGRBs. Our results also demonstrate that the remnant mass model underpredicts the disk mass for the DD2 equation of state, while they are within expected modeling errors for SFHo. The disruption limit itself, however, is not found to significantly differ from the predictions of the analytical model, unless remnant masses M rem ≲ 0.001 M ⊙ prove interesting observationally. In all of our simulations, any kilonova signal would be dim and most likely dominated by post-merger disk outflows.

GW230529_181500↗

Numerical simulation of steady supersonic flow over spinning bodies of revolution

A recently reported parabolized Navier-Stokes code has been employed to compute the supersonic flowfield about a spinning cone and spinning and nonspinning ogive cylinder and boattailed bodies of revolution at moderate incidence. The computations were performed for flow conditions where extensive measurements for wall pressure, boundary-layer velocity profiles, and Magnus force had been obtained. Comparisons between the computational results and experiment indicate excellent agreement for angles of attack up to 6 deg. At angles greater than 6 deg discrepancies are noted which are tentatively attributed to turbulence modeling errors. The comparisons for Magnus effects show that the code accurately predicts the effects of body shape for the selected models.

Sturek, W. B.↗

Model reduction of mechanical systems

A reduced model of a stable mechanical system with proportional damping represented in modal coordinates is developed, based on a procedure reported by Commault and Guerin (1978). In this model, model error is calculated a priori and is used to determine the dominant modes. Two examples are presented showing that reduced models generated as described will be better or at least as good as those produced by the popular modal cost analysis scheme of Skelton and Hughes (1980).

Yousuff, Ajmal↗