Search NASA⌕ Search

SEARCH · Search NASA

Results for “Widely Used”

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 307 records · Page 17

Regularized machine learning on molecular graph model explains systematic error in DFT enthalpies

Abstract A major goal of materials research is the discovery of novel and efficient heterogeneous catalysts for various chemical processes. In such studies, the candidate catalyst material is modeled using tens to thousands of chemical species and elementary reactions. Density Functional Theory (DFT) is widely used to calculate the thermochemistry of these species which might be surface species or gas-phase molecules. The use of an approximate exchange correlation functional in the DFT framework introduces an important source of error in such models. This is especially true in the calculation of gas phase molecules whose thermochemistry is calculated using the same planewave basis set as the rest of the surface mechanism. Unfortunately, the nature and magnitude of these errors is unknown for most practical molecules. Here, we investigate the error in the enthalpy of formation for 1676 gaseous species using two different DFT levels of theory and the ‘ground truth values’ obtained from the NIST database. We featurize molecules using graph theory. We use a regularized algorithm to discover a sparse model of the error and identify important molecular fragments that drive this error. The model is robust to rigorous statistical tests and is used to correct DFT thermochemistry, achieving more than an order of magnitude improvement.

36 MATERIALS SCIENCE↗

X-ray quantification of oxygen groups on diamond surfaces for quantum applications

Abstract Identifying the surface chemistry of diamond materials is increasingly important for device applications, especially quantum sensors. Oxygen-related termination species are widely used because they are naturally abundant, chemically stable, and compatible with stable nitrogen vacancy centres near the diamond surface. Diamond surfaces host a mixture of oxygen-related species, and the precise chemistry and relative coverage of different species can lead to dramatically different electronic properties, with direct consequences for near-surface quantum sensors. However, it is challenging to unambiguously identify the different groups or quantify the relative surface coverage. Here we show that a combination of x-ray absorption and photoelectron spectroscopies can be used to quantitatively identify the coverage of carbonyl functional groups on the { 100 } diamond surface. Using this method we reveal an unexpectedly high fraction of carbonyl groups ( > 9%) on a wide range of sample surfaces. Furthermore, through a combination of ab initio calculations and spectroscopic studies of engineered surfaces, we reveal unexpected complexities in the x-ray spectroscopy of oxygen terminated diamond surfaces. Of particular note, we find the binding energies of carbonyl-related groups on diamond differs significantly from other organic systems, likely resulting in previous misestimation of carbonyl fractions on diamond surfaces.

36 MATERIALS SCIENCE↗

Observations of phase changes in monoolein during high viscous injection

Serial crystallography of membrane proteins often employs high-viscosity injectors (HVIs) to deliver micrometre-sized crystals to the X-ray beam. Typically, the carrier medium is a lipidic cubic phase (LCP) media, which can also be used to nucleate and grow the crystals. However, despite the fact that the LCP is widely used with HVIs, the potential impact of the injection process on the LCP structure has not been reported and hence is not yet well understood. The self-assembled structure of the LCP can be affected by pressure, dehydration and temperature changes, all of which occur during continuous flow injection. These changes to the LCP structure may in turn impact the results of X-ray diffraction measurements from membrane protein crystals. To investigate the influence of HVIs on the structure of the LCP we conducted a study of the phase changes in monoolein/water and monoolein/buffer mixtures during continuous flow injection, at both atmospheric pressure and under vacuum. The reservoir pressure in the HVI was tracked to determine if there is any correlation with the phase behaviour of the LCP. The results indicated that, even though the reservoir pressure underwent (at times) significant variation, this did not appear to correlate with observed phase changes in the sample stream or correspond to shifts in the LCP lattice parameter. During vacuum injection, there was a three-way coexistence of the gyroid cubic phase, diamond cubic phase and lamellar phase. During injection at atmospheric pressure, the coexistence of a cubic phase and lamellar phase in the monoolein/water mixtures was also observed. The degree to which the lamellar phase is formed was found to be strongly dependent on the co-flowing gas conditions used to stabilize the LCP stream. A combination of laboratory-based optical polarization microscopy and simulation studies was used to investigate these observations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Medium Voltage Converter Inductor Insulation Design Considering Grid Insulation Requirements

Medium voltage SiC devices facilitate direct (without 50/60 Hz transformer) connection of the power electronics converter to the medium voltage grid using simple topology. Compared to the insulation design of medium voltage inductors that have been widely used in the power system, the insulation design of directly connected medium voltage converter filter inductors has more challenges. Although some works has been done discussing that, the grid insulation requirements on converter filter inductors are rarely discussed. This paper introduces the insulation design of a grid-side filter inductor for a 13.8 kV power conditioning system converter. The grid insulation requirements, including the short-duration power frequency overvoltage and the lightning impulse voltage, are considered in the design. To meet the requirements, the layer-to-layer insulation, winding-to-core/ground insulation, the air gap discharge between the winding and the core, as well as the local electrical field have been taken into consideration. Experimental tests are provided to validate the design.

Li, Haiguo↗

Fast All-sky Radiation Model for Solar applications (FARMS) [SWR-16-18]

The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.

Xie, Yu↗

ORNL Campus Sustainability and Decarbonization using Waste Heat Recovery from the Oak Ridge Leadership Computing Facility’s High-Performance Computing Data Center

Heat pumps are a clean and efficient technology that can be powered by renewable electricity to transfer heat using a refrigerant from one place to another by different heat sources, making buildings clean and environmentally friendly. With the support of the ORNL Laboratory Modernization Division, this project explored and evaluated an innovative solution that uses water-water cost-effective midtemperature heat pump (MTHP) technology to leverage the low-grade waste heat from ORNL Frontier and the data center to deliver 85°C hot water, which replaces hot steam generated using natural gas combustion boilers for water heating or space heating in the buildings of ORNL campus. Two scenarios were studied. In the first scenario, which considered the 5600-5700-5800 complex only, Carrier’s commercial 1,000 kW MTHP technology achieves more than 6,640 MWh/year energy savings, an emission reduction of 858 TCO2e/year CO2, and a payback time of 4.85 years. In the second scenario, which considered the 5600-5700-5800 complex and Buildings 5100, 5200, and 5300, the CO2 emission reduction is 1,483 TCO2e/year, the operating cost savings are $0.21 million annually, and the payback time is 3.74 years. Additionally, a comprehensive HP ShowCase Tool was developed for evaluating the optimal solution to improve sustainability and decarbonization of the buildings on the ORNL campus. The tool is an Excel-based tool integrated with VBA (Visual Basic for Applications) coding. The tool includes collected ORNL campus building information and an MTHP library, which comprises collected commercial and ORNL-defined MTHPs. The tool was used to evaluate the sustainability and decarbonization of the ORNL campus. The tool can be widely used or referenced for heat pump solutions and building decarbonization renovation strategies to modernize ORNL facilities and energy use–intensive equipment to enable efficient, sustainable, and resilient operations in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fast All-sky Radiation Model for Solar applications (FARMS) 2023 [SWR-16-18]

The Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute cloudy irradiance. Radiative transfer (RT) models simulating broadband solar radiation have been widely used by atmospheric scientists to model solar resources for various energy applications such as operational forecasting. Due to the complexity of solving the RT equation, the computation under cloudy conditions can be extremely time consuming though many approximations (e.g. two-stream approach and delta-M truncation scheme) have been utilized. Thus, a more efficient RT model is crucial for model developers as a new option for approximating solar radiation at the land surface with minimal loss of accuracy. We have developed a fast all-sky radiation model for solar applications (FARMS) using the simplified clear-sky RT model, REST2, and simulated cloud transmittances and reflectances from the Rapid Radiation Transfer Model (RRTM) with a sixteen-stream Discrete Ordinates Radiative Transfer (DISORT). Simulated lookup tables (LUTs) of cloud transmittances and reflectances were created by varying cloud optical thicknesses, cloud particle sizes, and solar zenith angles. Equations with optimized parameters were fitted to the cloud transmittances and reflectances to develop the model. Using this model the all-sky solar irradiance at the land surface can be computed rapidly by combining REST2 with the cloud transmittances and reflectances. This new RT model is more than 1000 times faster than those currently utilized in solar resource assessment and forecasting since it does not explicitly solve the RT equation for each individual cloud condition. Our results indicate the accuracy of the fast radiative transfer model is comparable to or better than two-stream approximation in term of computing cloud transmittance and solar radiation.

Xie, Yu↗

The development and use of metal-based probes for X-ray fluorescence microscopy

Abstract X-ray fluorescence microscopy (XFM) has become a widely used technique for imaging the concentration and distribution of metal ions in cells and tissues. Recent advances in synchrotron sources, optics, and detectors have improved the spatial resolution of the technique to <10 nm with attogram detection sensitivity. However, to make XFM most beneficial for bioimaging—especially at the nanoscale—the metal ion distribution must be visualized within the subcellular context of the cell. Over the years, a number of approaches have been taken to develop X-ray-sensitive tags that permit the visualization of specific organelles or proteins using XFM. In this review, we examine the types of X-ray fluorophore used, including nanomaterials and metal ions, and the approaches used to incorporate the metal into their target binding site via antibodies, genetically encoded metal-binding peptides, affinity labeling, or cell-specific peptides. We evaluate their advantages and disadvantages, review the scientific findings, and discuss the needs for future development.

36 MATERIALS SCIENCE↗

Accurate estimation of angular power spectra for maps with correlated masks

A common procedure when analyzing maps of the cosmic microwave background (CMB) or other cosmological signals is the need to remove ("mask") regions of the maps that are heavily contaminated, e.g., by non-cosmological foreground emission. After applying such a mask, one must account for its effect when inferring statistical properties of interest, such as the angular power spectrum of the field in the original map. A widely used approach to correct for such mask-induced effects was presented by Hivon et al. (2002), now widely known as the "MASTER" formalism. However, it is often the case that the map and mask are correlated in some way, such as point source masks used in CMB analyses, which have nonzero correlation with CMB secondary anisotropy fields and other mm-wave sky signals. In such situations, the MASTER approach gives biased results, as it assumes that the unmasked map and mask have zero correlation. While such effects have been discussed before with regard to specific physical models, here we derive a completely general formalism for any case where the map and mask are correlated. We show that our result ("reMASTERed") reconstructs ensemble-averaged angular power spectra to effectively exact precision, with significant improvements over traditional estimators for cases where the map and mask are correlated. An important consequence of our result is that for maps with correlated masks, it is no longer possible to invert a simple equation to obtain the true power spectrum from the observed (masked) power spectrum. Instead, our result necessitates the use of forward modeling from theory space into the observable domain of the masked power spectrum. We publicly release our software implementation of these results.

79 ASTRONOMY AND ASTROPHYSICS↗

Star formation rate and stellar mass calibrations based on infrared photometry and their dependence on stellar population age and extinction

The stellar mass (M $\star$ ) and the star formation rate (SFR) are among the most important features that characterize galaxies. Measuring these fundamental properties accurately is critical for understanding the present state of galaxies, their history, and future evolution. Infrared (IR) photometry is widely used to measure the M $\star$ and SFR of galaxies because the near-IR traces the continuum emission of the majority of their stellar populations (SPs), and the mid/far-IR traces the dust emission powered by star-forming activity. This work explores the dependence of the IR emission of galaxies on their extinction, and the age of their SPs. It aims to provide accurate and precise IR-photometry SFR and M $\star$ calibrations that account for SP age and extinction while providing quantification of their scatter. We used the CIGALE spectral energy distribution (SED) fitting code to create model SEDs of galaxies with a wide range of star formation histories, dust content, and interstellar medium properties. We fit the relations between M $\star$ and SFR with IR and optical photometry of the model-galaxy SEDs with the Markov chain Monte Carlo (MCMC) method. As an independent confirmation of the MCMC fitting method, we performed a machine-learning random forest (RF) analysis on the same data set. The RF model yields similar results to the MCMC fits, thus validating the latter. This work provides calibrations for the SFR using a combination of the WISE bands 1 and 3, or the JWST NIR-F200W and MIRI-F2100W. It also provides mass-to-light ratio calibrations based on the WISE band-1, the JWST NIR-F200W, and the optical u - r or g - r colors. These calibrations account for the biases attributed to the SP age, while they are given in the form of extinction-dependent and extinction-independent relations. The proposed calibrations show robust estimations while minimizing the scatter and biases throughout a wide range of SFRs and stellar masses. The SFR calibration offers better results, especially in dust-free or passive galaxies where the contributions of old SPs or biases from the lack of dust are significant. Similarly, the M $\star$ calibration yields significantly better results for dusty and high-SFR galaxies where dust emission can otherwise bias the estimations.

79 ASTRONOMY AND ASTROPHYSICS↗

How data science methods can improve the quality and efficiency of ICF and HEDP research

Data Science methods (many that are Bayesian based) are widely used in the physical sciences to estimate model parameters from experimental data, synthesize heterogeneous data, calibrate models, design experiments, and determine statistical significance of data. These methods provide a wealth of advantages over traditional analysis techniques because: 1) uncertainties are rigorously defined and propagated naturally through complex systems including covariance, 2) prior information is captured within the analysis framework (including rad-MHD and rad-hydro simulations), 3) competing models can be selected and/or ruled out using quantitative criteria, and 4) complex, heterogeneous data can be incorporated simultaneously. While these methods have been widely adopted as the gold standard in fields such as particle physics, astronomy, and biology, they have been slow to catch on in Inertial Confinement Fusion (ICF) and High Energy Density Physics (HEDP) research. Recently, several teams at LLNL, SNL, LANL, and the LLE have been exploring the use of these tools in their research and have found success. Here we propose that a concerted effort to consolidate these independent research efforts by developing and deploying common tools for use across the complex can revolutionize the way we approach data analysis, assimilation of theory and experiment, and decision making. The Bayesian formalism provides a means to accomplish this, but we are lacking certain infrastructure to make it happen on a large scale. Furthermore, once adopted, these techniques can be used to develop standards by which discoveries can be judged, similar to the so-called 5σ rule in high energy particle physics. Such standards may be used in the future to address the issue of unknown reproducibility in ICF and HED experiments caused by low shot rate and high cost per experiment. Our goals as a group are to advance the state of the art in HED measurement science by enabling: 1) better inferences from data with well-defined uncertainties, 2) better use of the data we have and continue to collect, 3) intelligent synthesis of data, 4) evaluation of the statistical significance of our data, and 5) informed decision making regarding the design of new experiments and instruments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

First Principle based Thermal Conductivity Modeling of Metal Alloys with Applications on Uranium Alloys

Thermal conductivity is an important materials property related to heat transport, which is essential to many applications, ranging from thermoelectrics to nuclear reactor materials. High- quality thermal conductivity data is critical to these materials and their associated technologies, including the nuclear fuel materials like traditional oxide fuels and metallic uranium (U) fuels, e.g. U-Zr and U-Mo alloys. And thermal conductivity modeling is widely used to interpolate or extrapolate experimental data, to obtain high-quality thermal conductivity data over wide temperature and composition range, and to understand the impacts of different factors including defects and microstructures. However, a general thermal conductivity model for metal alloys which can work regrading different phase components is still missing. Also, for U alloys, a thermal conductivity model working with different phases is needed. Therefore, in this work, we developed thermal conductivity models for metal alloys, based on ab-initio calculations, semi-classical physics rules, and limited experimental data. The goals of these models are to help obtain high- quality thermal conductivity data within a little experimental input as possible, have models that are extendable to varying microstructures, including different types of irradiation effects, and provide mechanistic understanding of heat transfer in the modeled alloys. In this work, our model solves several challenges in the development. The DFT-BTE approach is applied to decrease the reliance on experimental data and make the model extendable to composition changes and defects. A practical and efficient way to combine the DFT inputs with physics rules is pointed out in this work too. A staged approach, which starts from simple cases of elemental metals, then extends to solid solutions, different compound phases, and multi-phase mixtures, is presented to work with the metal alloys in different phase components. Our models are demonstrated respectively on aU for elemental metal model, on U-Zr and U-Mo alloys in aU temperature range for multi-phase mixture model, on high-temperature U-Zr, U-Nb, and U-Mo alloys in the body-centered cubic phase for concentrated solid solution model, and on irradiated U-Mo alloys for irradiated metal alloy model. All models show great agreement with experimental data. In these demonstrations, our model shows its advantages compared to previous empirical fitting model. Our model requires fewer experimental data, due to the inputs from DFT. The quantitative insights into the different physical factors are provided in our model, as it incorporates the electron and phonon scattering mechanisms. Our model also can be extended to incorporate the contributions of point defects, grain boundaries, and noble gas bubbles, to integrate their effects on heat transfer. This model can serve as both a foundation for understanding the more complex thermal conductivity of realistic U alloy fuels and a useful tool to guide further modeling of thermal conductivity to aid materials and device design.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Inelastic Neutron Scattering from Thin Film Biaxially Oriented Polyethylene Terephthalate

Recent interest in emerging processes for polymer manufacturing and bio-based chemistries for direct chemical recycling/upcycling has motivated new research focused on a deeper understanding of atomic-scale polymer properties and how they influence macroscopic phenomena. Uncovering the fundamental properties of polymers that give rise to macroscopic behavior could enable new pathways for improved recyclability or utilization of alternative “greener” polymer analogues. In this study, the neutron vibrational spectrum was measured for a film of biaxially oriented polyethylene terephthalate (BoPET) using inelastic neutron scattering (INS), to investigate the relationship between the structure and dynamics of a widely used polymer. Compared to conventional spectroscopic techniques, the use of INS is advantageous for polymeric materials due to the absence of selection rules (i.e., all transitions are allowed), broad-band energy range, and considerable sensitivity to hydrogen modes. In order to distinguish the vibrational modes caused by trans and gauche rotational isomerism, the normal modes of vibration were calculated from a density functional theory-optimized structure of crystalline PET (cPET), representative of the all-trans state, and compared with INS from “highly crystalline” PET powder. Although in- and out-of-plane wagging of hydrogens on the ring structure exhibit significant contribution to both BoPET and cPET spectra, the wagging, rocking, and twisting modes of hydrogen on the ethylene glycol group are, in most cases, conformation-specific. These results were further rationalized by investigating the role of hyperconjugation in stabilizing both conformations using the natural bond order method. Here, through comparison of experimental and calculated INS results, this work provides the fundamental basis for discovering the role of structure and dynamics in shaping the macroscopic properties of PET and polymer analogues.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elucidating the Role of Halides and Iron during Radiolysis-Driven Oxidative Etching of Gold Nanocrystals Using Liquid Cell Transmission Electron Microscopy and Pulse Radiolysis

Graphene liquid cell transmission electron microscopy (TEM) has enabled the observation of a variety of nanoscale transformations. Yet understanding the chemistry of the liquid cell solution and its impact on the observed transformations remains an important step toward translating insights from liquid cell TEM to benchtop chemistry. Gold nanocrystal etching can be used as a model system to probe the reactivity of the solution. FeCl 3 has been widely used to promote gold oxidation in bulk and liquid cell TEM studies, but the roles of the halide and iron species have not been fully elucidated. In this work, we observed the etching trajectories of gold nanocrystals in different iron halide solutions. We observed an increase in gold nanocrystal etch rate going from Cl - - to Br - - to I - -containing solutions. Furthermore, this is consistent with a mechanism in which the dominant role of halides is as complexation agents for oxidized gold species. Additionally, the mechanism through which FeCl 3 induces etching in liquid cell TEM remains unclear. Ground-state bleaching of the Fe(III) absorption band observed through pulse radiolysis indicates that iron may react with Cl 2 · - radicals to form an oxidized transient species under irradiation. Complete active space self-consistent field (CASSCF) calculations indicate that the FeCl 3 complex is oxidized to an Fe species with an OH radical ligand. Together our data indicate that an oxidized Fe species may be the active oxidant, while halides modulate the etch rate by tuning the reduction potential of gold nanocrystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mitigating challenges in aberration-corrected electron-beam lithography on electron-opaque substrates

Aberration-corrected electron-beam lithography (AC-EBL) using ultra-thin electron transparent membranes has achieved single-digit nanometer resolution in two widely used electron-beam resists: poly (methyl methacrylate) (PMMA) and hydrogen silsesquioxane. On the other hand, AC-EBL implementation on thick, electron-opaque substrates is appealing for conventional top-down fabrication of quantum devices with nanometer-scale features. To investigate the performance of AC-EBL on thick substrates, we measured the lithographic point spread function of a 200 keV aberration-corrected scanning transmission electron microscope by defining both positive and negative patterns in PMMA thin films, spin-cast on thick SiO 2 /Si substrates. We present the problems encountered during pre-exposure beam focusing and discuss methods to overcome them. In addition, applying some of these methods using commercial 50 nm thick SiN X membranes with thick Si support frames, we printed arrays of holes in PMMA with pitches around 26 nm on SiN X /Si substrates with increasing Si thickness. Here, our results show that proximity effects from even 50 nm thick SiN X membranes limit hole arrays to 20 nm pitch; however, down to this limit, the effect of the substrate thickness on the pattern quality is minimal. These results highlight the need for novel resists less susceptible to proximity effects, or resists which can be used directly, after development, as the dielectric material in periodic gates in 2D quantum devices.

2D quantum devices↗

Enabling Scientific Applications with Performance-Portability and High-Productivity for Multi-GPU Programming with JACC.Multi

This work bridges the gap between multi-GPU computing and high-productivity, performance-portable programming solutions. Our goal is to enhance scientific applications with a productive and portable solution—program once, deploy everywhere—for multi-GPU programming with no cost to programmability. To accomplish this, we implemented JACC.Multi, which is part of the Julia for ACCelerators (JACC) performance-portable framework. JACC. Multi is the only high-level, portable metaprogramming solution that targets multi-GPU environments and is integrated in a readily accessible programming language (e.g., Julia language). With transparent GPU-to-GPU communication, JACC. Multi is optimized for scientific application workloads and is portable for NVIDIA and AMD accelerators. For the evaluation, we use two modern multi-GPU systems: Hudson, which features two NVIDIA H100 Hopper GPUs per node, and Frontier, which features four AMD MI250X GPUs per node, each with two Graphics Compute Dies (GCDs) for a total of eight GCDs per node. Additionally, as part of the evaluation, we use JACC (one GPU), MPI+JACC, and JACC. Multi codes that implement well-known and widely used scientific algorithms/kernels such as the conjugate gradient algorithm and an explicit forward Euler solver that requires GPU-to-GPU communication. Overall, JACC. Multi codes achieve better performance than MPI+JACC codes and significant speedups over JACC (one GPU), with up to 1.9× on Hudson and 6× on Frontier.

Valero Lara, Pedro [ORNL] (ORCID:0000000214794310)↗

Traffic Signal Control With Adaptive Online-Learning Scheme Using Multiple-Model Neural Networks

This article proposes a new traffic signal control algorithm to deal with unknown-traffic-system uncertainties and reduce delays in vehicle travel time. Unknown-traffic-system dynamics are approximated using a recurrent neural network (NN). To accurately identify the traffic system model, an online-learning scheme is developed to switch among a set of candidate NNs (i.e., multiple-model NNs) based on their estimation errors. Then, a bank of optimal signal-timing controllers is designed based on the online identification of the traffic system. Simulation studies have been carried out for the obtained control strategies using multiple-model NNs, and the desired results have been obtained. Moreover, compared with the widely used actuated traffic signal control schemes, it is shown that the proposed method can reduce vehicle travel delays and improve traffic system robustness.

99 GENERAL AND MISCELLANEOUS↗