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At least 1,459 records · Page 81

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Hejre, we introduce physics-informed neural networks – neural networks that are trained to solve supervised learning tasks while respecting any given laws of physics described by general nonlinear partial differential equations. In this work, we present our developments in the context of solving two main classes of problems: data-driven solution and data-driven discovery of partial differential equations. Depending on the nature and arrangement of the available data, we devise two distinct types of algorithms, namely continuous time and discrete time models. The first type of models forms a new family of data-efficient spatio-temporal function approximators, while the latter type allows the use of arbitrarily accurate implicit Runge–Kutta time stepping schemes with unlimited number of stages. Moreover, the effectiveness of the proposed framework is demonstrated through a collection of classical problems in fluids, quantum mechanics, reaction–diffusion systems, and the propagation of nonlinear shallow-water waves.

97 MATHEMATICS AND COMPUTING↗

Power generation forecasting for solar plants based on Dynamic Bayesian networks by fusing multi-source information

A Dynamic Bayesian network (DBN) model for solar power generation forecasting in solar plants is proposed in this paper. The key idea is to fuse sensor data, operational indicators, meteorological data, lagged output power information, and model errors for more accurate short-term (e.g., hours) and mid-term (e.g., days to weeks) power generation forecasting. The proposed DBN augments automated data-driven structure learning with expert knowledge encoding using continuous and categorical data given constraints to represent causal relationships within a solar inverter system. Additionally, an error compensation mechanism is proposed to capture temporal fluctuation. The effectiveness of the DBN on solar power generation forecasting was evaluated by rolling window analysis with one-year testing data collected from a local solar plant. The proposed DBN is compared with four state-of-art methods including support-vector regression (SVR), k-nearest neighbors (kNN), artificial neural network (ANN), and long short-term memory (LSTM) models. The result show that the proposed DBN achieves better accuracy in general, and it is not as data-hungry as some neural network-based models. The proposed DBN is also shown to have robust and consistent forecasting power with different forecasting horizons. The accuracy is 92% - 95% from one hour to one week ahead forecasting.

14 SOLAR ENERGY↗

Study of the light scalar a 0 ( 980 ) through the decay D 0 → a 0 ( 980 ) − e + ν e with a 0 ( 980 ) − → η π −

Using 7.93 fb − 1 of e + e − collision data collected at a center-of-mass energy of 3.773 GeV with the BESIII detector, we present an analysis of the decay D 0 → η π − e + ν e . The branching fraction of the decay D 0 → a 0 ( 980 ) − e + ν e with a 0 ( 980 ) − → η π − is measured to be ( 0.86 ± 0.1 7 stat ± 0.0 5 syst ) × 10 − 4 . The decay dynamics of this process is studied with a single-pole parametrization of the hadronic form factor and the Flatté formula describing the a 0 ( 980 ) line shape in the differential decay rate. The product of the form factor f + a 0 ( 0 ) and the Cabibbo-Kobayashi-Maskawa matrix element | V c d | is determined for the first time with the result f + a 0 ( 0 ) | V c d | = 0.126 ± 0.01 3 stat ± 0.00 3 syst . Published by the American Physical Society 2025

Ablikim, M.↗

Interplay Between Antimagnetic and Collective Rotation in {sup 58}Fe

The self-consistent tilted axis cranking covariant density functional theory based on the point-coupling interaction PC-PK1 is applied to investigate the possible existence of antimagnetic rotation in the nucleus Fe-58. The observed data for Bands 3 and 4 are reproduced well with two assigned configurations. It is found that the interplay between antimagnetic rotation and collective motion plays an essential role in both bands due to the presence of considerable deformation. In particular, for Band 4, collective rotation is dominant in the competition with antimagnetic rotation. Moreover, it is shown that the behavior of the ratios between the dynamic moments of inertia and the B(E2) values reflects the interplay between antimagnetic and collective rotation.

antimagnetic rotation↗

RetSynth: determining all optimal and sub-optimal synthetic pathways that facilitate synthesis of target compounds in chassis organisms

The efficient biological production of industrially and economically important compounds is a challenging problem. Brute-force determination of the optimal pathways to efficient production of a target chemical in a chassis organism is computationally intractable. Many current methods provide a single solution to this problem, but fail to provide all optimal pathways, optional sub-optimal solutions or hybrid biological/non-biological solutions. Here we present RetSynth, software with a novel algorithm for determining all optimal biological pathways given a starting biological chassis and target chemical. By dynamically selecting constraints, the number of potential pathways scales by the number of fully independent pathways and not by the number of overall reactions or size of the metabolic network. This feature allows all optimal pathways to be determined for a large number of chemicals and for a large corpus of potential chassis organisms. Additionally, this software contains other features including the ability to collect data from metabolic repositories, perform flux balance analysis, and to view optimal pathways identified by our algorithm using a built-in visualization module. This software also identifies sub-optimal pathways and allows incorporation of non-biological chemical reactions, which may be performed after metabolic production of precursor molecules. The novel algorithm designed for RetSynth streamlines an arduous and complex process in metabolic engineering. Our stand-alone software allows the identification of candidate optimal and additional sub-optimal pathways, and provides the user with necessary ranking criteria such as target yield to decide which route to select for target production. Furthermore, the ability to incorporate non-biological reactions into the final steps allows determination of pathways to production for targets that cannot be solely produced biologically. With this comprehensive suite of features RetSynth exceeds any open-source software or webservice currently available for identifying optimal pathways for target production.

59 BASIC BIOLOGICAL SCIENCES↗

Reduction of blade-vortex interaction noise using higher harmonic pitch control

An acoustics test using an aeroelastically scaled rotor was conducted to examine the effectiveness of higher harmonic blade pitch control for the reduction of impulsive blade-vortex interaction (BVI) noise. A four-bladed, 110 in. diameter, articulated rotor model was tested in a heavy gas (Freon-12) medium in Langley's Transonic Dynamics Tunnel. Noise and vibration measurements were made for a range of matched flight conditions, where prescribed (open-loop) higher harmonic pitch was superimposed on the normal (baseline) collective and cyclic trim pitch. For the inflow-microphone noise measurements, advantage was taken of the reverberance in the hard walled tunnel by using a sound power determination approach. Initial findings from on-line data processing for three of the test microphones are reported for a 4/rev (4P) collective pitch control for a range of input amplitudes and phases. By comparing these results to corresponding baseline (no control) conditions, significant noise reductions (4 to 5 dB) were found for low-speed descent conditions, where helicopter BVI noise is most intense. For other rotor flight conditions, the overall noise was found to increase. All cases show increased vibration levels.

Brooks, Thomas F.↗

Reduction of blade-vortex interaction noise through higher harmonic pitch control

An acoustics test using an aeroelastically scaled rotor was conducted to examine the effectiveness of higher harmonic blade pitch control for the reduction of impulsive blade-vortex interaction (BVI) noise. A four-bladed, 110 in. diameter, articulated rotor model was tested in a heavy gas (Freon-12) medium in Langley's Transonic Dynamics Tunnel. Noise and vibration measurements were made for a range of matched flight conditions, where prescribed (open-loop) higher harmonic pitch was superimposed on the normal (baseline) collective and cyclic trim pitch. For the inflow-microphone noise measurements, advantage was taken of the reverberance in the hard walled tunnel by using a sound power determination approach. Initial findings from on-line data processing for three of the test microphones are reported for a 4/rev (4P) collective pitch control for a range of input amplitudes and phases. By comparing these results to corresponding baseline (no control) conditions, significant noise reductions (4 to 5 dB) were found for low-speed descent conditions, where helicopter BVI noise is most intense. For other rotor flight conditions, the overall noise was found to increase. All cases show increased vibration levels.

Brooks, Thomas F.↗

The Ulysses mission - In-ecliptic phase

Coordinated data analyses from the initial in-ecliptic phase of the Ulysses mission are presented with special attention given to measurements of particles and fields in interplanetary space. The collection of papers presents the results of observations of large solar flares and effects related to solar wind, and some results are synopsized. The charged-particle instrumentation on the spacecraft is shown to have good dynamic range and energy coverage as demonstrated by a sample proton-energy spectrum.

Wenzel, K.-P.↗

Validation of Multi-Dimensional Stirling Engine Design Codes: Measurements in the 90-Degree Turn Test Section

The work to be presented herein was motivated largely by a desire to improve the understanding of oscillatory fluid mechanics inside a Stirling engine. To this end, a CFD project was undertaken at Cleveland State University with the goal of accurately predicting the fluid dynamics within an engine or engine component. Along with the CFD efforts, a code validation project was undertaken at the University of Minnesota. The material covered herein consists of four main parts. In section 1, an experimental investigation of a small aspect ratio impinging jet is discussed. Included in this discussion is a description of the test facilities and instrumentation. A presentation of the collected data is given and comments are made. Next, in section 2, a parallel experimental investigation is presented in which the same geometry as that of section 1 is used, but the flow conditions are changed from steady unidirectional flow to sinusoidally oscillating flow. In section Two, collected data are presented and comments are made. In section 3, a comparison is made between the results of sections 1 and 2, namely, sinusoidally oscillating flow results are compared to steady, unidirectional flow results from the same geometry. Finally, in section 4, a comparison is made between experimentally collected data (the main subject of this work) and CFD generated results. Furthermore, in appendix A, an introductory description of the primary measurement tool used in the experimental process the hot wire anemometer is given for the unfamiliar. The anemometer calibration procedure is described in appendix B. A portfolio of data reduction and data processing codes is provided in appendix C and lastly, a DVD and a roadmap of its contents is provided in an appendix D. 1.0 Unidirectional Flow Investigations 1.1 Introduction This unidirectional experimental program was undertaken to complement an oscillatory flow investigation conducted at the University of Minnesota. The oscillatory investigation is discussed thoroughly in section 2. We defer the description of the motivation behind these experiments until the introduction of section 2. The work that is discussed in this thesis began (chronologically) with oscillatory flow visualization experiments. It was decided that it would be valuable and important to investigate the flow under unidirectional conditions in the same geometry as that of the oscillatory experiments. The thought was that the unidirectional case would be less complicated to model with a CFD program (a moving boundary would be replaced with a steady state boundary condition). Thus, a series of unidirectional experiments were carried out to capture the important features of the flow within the test section. The purpose of these experiments was to provide a data set for comparison to CFD generated velocity fields. Hot-wire anemometry data were taken and flow visualization was conducted as a standard for code validation. The flow geometry was simple, such that it could be easily gridded in a CFD program. However, the geometry provided separation and transition zones, shear layers and recirculation zones. These characteristics made the flow complex and challenging for CFD computation. We comment that the order of experiments that produced this report is as follows: experimental flow visualization under oscillatory flow conditions was carried out; this was followed by unidirectional flow visualization and hot wire anemometry; finally, oscillatory hot wire anemometry was conducted. We present the results out of chronological order for the following reason: the unidirectional results are easier

Simon, Terrence W.↗

An on-board processor for a spaceborne Doppler precipitation radar : requirements and preliminary design

Use of Doppler velocity measurement in spaceborne precipitation radar is highly desirable, since it can allow more accurate retrieval of atmospheric latent heating, which depends on both cloud and rain microphysical processes and on dynamical processes, namely, vertical updrafts and downdrafts. However, if the rain within the antenna beam is very non-uniform, biases can result with conventional pulse-pair processing, and more sophisticated processing is required. The solution is a time-frequency approach, which uses the full Doppler spectrum at each point in time. Since precipitation radars normally operate continuously and collect large amounts of data, real-time, on-board processing of data is needed to reduce the data rate. The objective of this work is to develop an on-board data processor for spaceborne Doppler precipitation radar, using field-programmable gate array (FPGA) technology. This paper describes the simulations and analysis that have been completed during the first year of the project. This includes both analytical calculations and bit-true simulations that allow the effects of finite word length to be explored. Tradeoffs have also been considered between speed and space within the chosen FPGA part. The results of these analyses have been used to develop a complete set of requirements for the processor. Initial design work has begun, based on these requirements. The design is being implemented in Verilog, and a description of this early design effort is also be given.

on-board processing↗

Space Shuttle Systems Engineering Processes for Liftoff Debris Risk Mitigation

This slide presentation reviews the systems engineering process designed to reduce the risk from debris during Space Shuttle Launching. This process begins the day of launch from the tanking to the vehicle tower clearance. Other debris risks (i.e., Ascent, and micrometeoroid orbital debit) are mentioned) but are not the subject of this presentation. The Liftoff debris systems engineering process and an example of how it works are reviewed (i.e.,STS-119 revealed a bolt liberation trend on the Fixed Service Structure (FSS) 275 level elevator room). The process includes preparation of a Certification of Flight Readiness (CoFR) that includes (1) Lift-off debris from previous mission dispositioned, (2) Flight acceptance rationale has been provided for Lift-off debris sources/causes (3) Lift-off debris mission support documentation, processes and tools are in place for the up-coming mission. The process includes a liftoff debris data collection that occurs after each launch. This includes a post launch walkdown, that records each liftoff debris, and the entry of the debris into a database, it also includes a review of the imagery from the launch, and a review of the instrumentation data. There is also a review of the debris transport analysis process, that includes temporal and spatial framework and a computational fluid dynamics (CFD) analysis. which incorporates a debris transport analyses (DTA), debris materials and impact tests, and impact analyses.

Mitchell, Michael↗

UAV Trajectory Modeling Using Neural Networks

Massive small unmanned aerial vehicles are envisioned to operate in the near future. While there are lots of research problems need to be addressed before dense operations can happen, trajectory modeling remains as one of the keys to understand and develop policies, regulations, and requirements for safe and efficient unmanned aerial vehicle operations. The fidelity requirement of a small unmanned vehicle trajectory model is high because these vehicles are sensitive to winds due to their small size and low operational altitude. Both vehicle control systems and dynamic models are needed for trajectory modeling, which makes the modeling a great challenge, especially considering the fact that manufactures are not willing to share their control systems. This work proposed to use a neural network approach for modelling small unmanned vehicle's trajectory without knowing its control system and bypassing exhaustive efforts for aerodynamic parameter identification. As a proof of concept, instead of collecting data from flight tests, this work used the trajectory data generated by a mathematical vehicle model for training and testing the neural network. The results showed great promise because the trained neural network can predict 4D trajectories accurately, and prediction errors were less than 2:0 meters in both temporal and spatial dimensions.

Neural Networks↗

Continuous and discrete modeling of HIV-1 decline on therapy

Mathematical models have shed light on the dynamics of HIV- 1 infection in vivo. In this paper, we generalize continuous mathematical models of drug therapy for HIV-1 by Perelson et al. (Science 271:1582–1586, 1996) and Perelson and Nelson (SIAM Rev 41:3–44, 1999) on time scales, i.e., a nonempty closed subset of real numbers in order to derive new discrete models that predict the total concentration of plasma virus as a function of time. Here, one of our main goals is to compare discrete mathematical models with the continuous model in Perelson et al. (1996) where HIV infected patients were given protease inhibitors and sampled frequently thereafter. For the comparison, we use experimental data collected in Perelson et al. (1996) and estimate the parameters such as the virion clearance rate and the rate of loss of infected cells by fitting the total concentration of plasma virus to this data set. Our results show that discrete systems describe the best fit. In the previous models of this study, the efficacy of protease inhibitor is assumed to be perfect. Motivated by Perelson and Nelson (1999), we end the paper with a mathematical model of imperfect protease inhibitor and reverse transcriptase (RT) inhibitor combination therapy of HIV-1 infection on time scales with its stability analysis.

60 APPLIED LIFE SCIENCES↗

Quantifying shallow subsurface water and heat dynamics using coupled hydrological-thermal-geophysical inversion

Improving our ability to estimate the parameters that control water and heat fluxes in the shallow subsurface is particularly important due to their strong control on recharge, evaporation and biogeochemical processes. The objectives of this study are to develop and test a new inversion scheme to simultaneously estimate subsurface hydrological, thermal and petrophysical parameters using hydrological, thermal and electrical resistivity tomography (ERT) data. The inversion scheme – which is based on a nonisothermal, multiphase hydrological model – provides the desired subsurface property estimates in high spatiotemporal resolution. A particularly novel aspect of the inversion scheme is the explicit incorporation of the dependence of the subsurface electrical resistivity on both moisture and temperature. The scheme was applied to synthetic case studies, as well as to real datasets that were autonomously collected at a biogeochemical field study site in Rifle, Colorado. At the Rifle site, the coupled hydrological-thermal-geophysical inversion approach well predicted the matric potential, temperature and apparent resistivity with the Nash–Sutcliffe efficiency criterion greater than 0.92. Synthetic studies found that neglecting the subsurface temperature variability, and its effect on the electrical resistivity in the hydrogeophysical inversion, may lead to an incorrect estimation of the hydrological parameters. The approach is expected to be especially useful for the increasing number of studies that are taking advantage of autonomously collected ERT and soil measurements to explore complex terrestrial system dynamics.

58 GEOSCIENCES↗

Forecasting Responses of a Northern Peatland Carbon Cycle to Elevated CO 2 and a Gradient of Experimental Warming

The ability to forecast ecological carbon cycling is imperative to land management in a world where past carbon fluxes are no longer a clear guide in the Anthropocene. However, carbon–flux forecasting has not been practiced routinely like numerical weather prediction. This study explored (1) the relative contributions of model forcing data and parameters to uncertainty in forecasting flux– versus pool–based carbon cycle variables and (2) the time points when temperature and CO 2 treatments may cause statistically detectable differences in those variables. We developed an online forecasting workflow (Ecological Platform for Assimilation of Data (EcoPAD)), which facilitates iterative data–model integration. EcoPAD automates data transfer from sensor networks, data assimilation, and ecological forecasting. We used the Spruce and Peatland Responses Under Changing Experiments data collected from 2011 to 2014 to constrain the parameters in the Terrestrial Ecosystem Model, forecast carbon cycle responses to elevated CO 2 and a gradient of warming from 2015 to 2024, and specify uncertainties in the model output. Our results showed that data assimilation substantially reduces forecasting uncertainties. Interestingly, we found that the stochasticity of future external forcing contributed more to the uncertainty of forecasting future dynamics of C flux–related variables than model parameters. However, the parameter uncertainty primarily contributes to the uncertainty in forecasting C pool–related response variables. Given the uncertainties in forecasting carbon fluxes and pools, our analysis showed that statistically different responses of fast–turnover pools to various CO 2 and warming treatments were observed sooner than slow–turnover pools. In conclusion, our study has identified the sources of uncertainties in model prediction and thus leads to improve ecological carbon cycling forecasts in the future.

54 ENVIRONMENTAL SCIENCES↗

Evidence for collective multiparticle correlations in p – Pb collisions

The second-order azimuthal anisotropy Fourier harmonics, v₂, are obtained in p−Pb and PbPb collisions over a wide pseudorapidity (η) range based on correlations among six or more charged particles. The p-Pb data, corresponding to an integrated luminosity of 35 nb⁻¹, were collected during the 2013 LHC p-Pb run at a nucleon-nucleon center-of-mass energy of 5.02 TeV by the CMS experiment. A sample of semiperipheral PbPb collision data at √s = 2.76 TeV, corresponding to an integrated luminosity of 2.5 μb⁻¹ and covering a similar range of particle multiplicities as the p−Pb data, is also analyzed for comparison. The six- and eight-particle cumulant and the Lee-Yang zeros methods are used to extract the v₂ coefficients, extending previous studies of two- and four-particle correlations. For both the p−Pb and PbPb systems, the v₂ values obtained with correlations among more than four particles are consistent with previously published four-particle results. These data support the interpretation of a collective origin for the previously observed long-range (large Δη) correlations in both systems. The ratios of v2 values corresponding to correlations including different numbers of particles are compared to theoretical predictions that assume a hydrodynamic behavior of a p−Pb system dominated by fluctuations in the positions of participant nucleons. These results provide new insights into the multiparticle dynamics of collision systems with a very small overlapping region.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Gray-Box Approach for Thermal Modelling of Buildings for Applications in District Heating and Cooling Networks

District-heating-and-cooling (DHC) systems are a proven energy solution that has been deployed for many years in a growing number of urban areas worldwide. They comprise a variety of technologies that seek to develop synergies between the production and supply of heat, cooling, domestic hot water and electricity. Although the benefits of DHC systems are significant and have been widely acclaimed, yet the full potential of modern DHC systems remains largely untapped. There are several opportunities for development of energy efficient DHC systems, which will enable the effective exploitation of alternative renewable resources, waste heat recovery, etc., in order to increase the overall efficiency and facilitate the transition towards the next generation of DHC systems. This motivated the need for modelling these complex systems. Large-scale modelling of DHC-networks is challenging, as it has several components such as buildings, pipes, valves, heating source, etc., interacting with each other. In this paper, we focus on building modelling. In particular, we present a gray-box methodology for thermal modelling of buildings. Gray-box modelling is a hybrid of data driven and physics based models where, coefficients of the equations from physics based models are learned using data. This approach allows us to capture the dynamics of the buildings more effectively as compared to pure data driven approach. Additionally, this approach results in a simpler models as compared to pure physics based models. We first develop the individual components of the building such as temperature evolution, flow controller, etc. These individual models are then integrated in to the complete gray-box model for the building. The model is validated using data collected from one of the buildings at Lule{\aa}, a city on the coast of northern Sweden.

Saurav, Kumar↗

Quality-Controlled Upper-Air Sounding Dataset for DYNAMO/CINDY/AMIE: Development and Corrections

The upper-air sounding network for DYNAMO (Dynamics of the Madden-Julian Oscillation or MJO) has provided an unprecedented set of observations for studying the MJO over the Indian Ocean (IO) where coupling of this oscillation with deep convection first occurs. With 72 sounding sites and dropsonde data from 13 aircraft mission, the sonde network covers the tropics from Eastern African to the West Pacific. In total nearly 26,000 sondes were collected from this network during the experiment’s 6-month extended observing period (from October 2011 to March 2012). Slightly more than half of the sondes, collected from 33 sites, are at high vertical resolution. Rigorous post-field phase processing of the sonde data included several levels of quality checks and a variety of corrections which address a number of issues (e.g., daytime dry bias, baseline surface data errors, ship deck-heating effects, artificial dry spikes in slow ascent sondes). Because of the importance of an accurate description of the moisture field in meeting the scientific goals of the experiments, particular attention is given to humidity correction and its validation. The humidity corrections, though small relative to some previous field campaigns, produced high fidelity moisture analyses in which sonde precipitable water compared well with independent estimates. An assessment of model operational analyses moisture using corrected sonde data shows an overall good agreement with the exception at upper-levels where model moisture and clouds are more abundant than the sounding data would indicate.

dataset↗