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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.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Simulation study for particle identification with the dRICH of the ePIC experiment at the EIC

The dual-radiator Imaging Cherenkov detector (dRICH), employing an aerogel and a gas radiator, is a key component of the forward particle identification system for the ePIC experiment at the Electron-Ion Collider (EIC). This study evaluates the dRICH performance using Geant4 simulations in the context of the global ePIC simulation stack, focusing on the optimization of the aerogel radiator and the impact of sensor noise. We compare two aerogel configurations: the initial design (n = 1.019) and the current default (n = 1.026). The latter, characterized by improved optical properties and a higher refractive index, demonstrates enhanced π/K separation at high momenta, effectively extending the operational overlap with the C 2 F 6 gas radiator (n = 1.00076 at 25 °C, as implemented in the simulation software). Additionally, the study investigates the impact of Silicon Photomultiplier (SiPM) dark noise, showing that a 300 kHz noise rate per 3mm x 3mm channel leads to a moderate reduction (approximately 1.5 GeV/c) in the 3σ separation threshold. These results validate the current dRICH design and quantify the purity levels achievable for both radiators under expected experimental conditions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

AIS-based characterization of navigation conflicts along the US Atlantic Coast prior to development of wind energy

This study characterizes navigation conflicts in a region with a large traffic volume along the US Atlantic Coast, utilizing Automated Identification System (AIS) data for 2010. The region includes areas proposed for wind energy development. The characterization could be useful in evaluating the effect of offshore wind areas on navigation conflicts. The study processes the AIS data to provide pairwise comparisons of vessel interactions (encounters and near-misses) as they occurred. Using the vessel encounter data, analyses are made using a ‘blind’ vessel assumption to evaluate the potential for both near-misses and collisions. Then statistical analyses are made to estimate the point values and uncertainty for each type of encounter (crossing, head-on, overtaking). Examination of the frequency/number of collisions from actual observations is made. The examination of actual near-misses, potential near-misses, and potential collisions provides comparable results in the number of near-misses and collisions. The potential near-miss analyses include an examination of the timing of responses made by vessels to prevent near-misses. This informed the statistical analysis but may also have utility in the simulation of navigation conflicts.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Maritime Route Delineation using AIS Data from the Atlantic Coast of the US

This study examines maritime routes between ports along the Atlantic coast of the US, utilising Automated Identification System (AIS) data for the years 2010 through 2012. The delineation of vessel routes conducted in this study was motivated by development planned for offshore Wind Energy Areas (WEAs) along the Atlantic coast of the US and the need to evaluate the effect of these development areas on commercial shipping. To this end, available AIS data were processed to generate commercial vessel tracks for individual vessels, though cargo vessels are the focus in this study. The individual vessel tracks were sampled at transects placed along the Atlantic coast. The transect samples were analysed and partitioned by voyages between Atlantic ports to facilitate computation of vessel routes between ports. The route boundary analysis utilised a definition from UK guidance in which routes' boundaries encompassed 95% of the vessel traffic between ports. In addition to delineating route boundaries, we found multi-modal transverse distributions of vessels for well-travelled routes, which indicated preference for lanes of travel within the delineated routes.

Coastal↗
DOE OSTI2021

Dynamic Process Intensification via Data-Driven Dynamic Optimization: Concept and Application to Ternary Distillation

Process intensification is a design philosophy aimed at making chemical processes safer and more efficient. Its implementation often results in significant modifications to the design and structure of the process, with several conventional unit operations occurring in the same physical device. Traditionally, process intensification has focused on steady-state operation. In our previous works, we introduced dynamic process intensification (DPI) as a new intensification paradigm based on operational changes for conventional or intensified units. DPI is predicated on switching operation between two auxiliary steady states selected via a steady-state optimization calculation that ensures that the system generates, on average and over time, the same products as in nominal steady-state operation, but with favorable economics. This paper extends the DPI concept and introduces a novel dynamic optimization-based DPI strategy (Do-DPI) that involves imposing a true cyclic operation rather than switching between two discrete states. We discuss its implementation using surrogate dynamic models learned via system identification. Here, an extensive case study concerning a ternary distillation column separating a canonical hydrocarbon mixture shows that Do-DPI can reduce energy use by more than 4% relative to steady-state operation, with no significant deviations in product quality and production rate.

42 ENGINEERING↗
DOE OSTI2014

High voltage stability performance of a gamma ray detection device

An industrial grade digital radiation survey meter device is currently being developed at Malaysian Nuclear Agency. This device used a cylindrical type Geiger Mueller (GM) which acts as a detector. GM detector operates at relatively high direct current voltages depend on the type of GM tube. This thin/thick walled cylindrical type of GM tube operates at 450-650 volts range. Proper value and stability performance of high voltage are important parameters to ensure that this device give a reliable radiation dose measurement. This paper will present an assessment of the stability and performance of the high voltage supply for radiation detector. The assessment is performed using System Identification tools box in MATLAB and mathematical statistics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Implementation of EPICS based vacuum control system for variable energy cyclotron centre, Kolkata

The vacuum system of the Room Temperature (K = 130) Cyclotron of Variable Energy Cyclotron Centre is comprised of vacuum systems of main machine and Beam Transport System. The vacuum control system is upgraded to a PLC based Automated system from the initial relay based Manual system. The supervisory control of the vacuum system is implemented in Experimental Physics and Industrial Control System (EPICS). An EPICS embedded ARM based vacuum gauge controller is developed to mitigate the requirement of vendor specific gauge controller for gauges and also for seamless integration of the gauge controllers with the control system. A set of MS-Windows ActiveX components with embedded EPICS Channel Access interface are developed to build operator interfaces with less complex programming and to incorporate typical Windows feature, e.g., user authentication, file handling, better fonts, colors, mouse actions etc. into the operator interfaces. The control parameters, monitoring parameters, and system interlocks of the system are archived in MySQL based EPICS MySQL Archiver developed indigenously. In this paper, we describe the architecture, the implementation details, and the performance of the system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Multi input single output model predictive control of non-linear bio-polymerization process

This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state space model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Beam particle identification and tagging of incompletely stripped heavy beams with HEIST

A challenge preventing successful inverse kinematics measurements with heavy nuclei that are not fully stripped is identifying and tagging the beam particles. For this purpose, the HEavy ISotope Tagger (HEIST) has been developed. HEIST utilizes two micro-channel plate timing detectors to measure the time-of-flight, a multi-sampling ion chamber to measure energy loss, and a high-purity germanium detector to identify isomer decays and calibrate the isotope identification system. HEIST has successfully identified 198 Pb and other nearby nuclei at energies of about 75 MeV/A. In the experiment discussed, a typical cut containing 89% of all 198 Pb 80+ in the beam had a purity of 86%. We examine the issues of charge state contamination. Here, the observed charge state populations of these ions are presented and, using an adjusted beam energy, are well described by the charge state model GLOBAL.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Nonlinear elasticity and damping govern ultrafast dynamics in click beetles

Many small animals use springs and latches to overcome the mechanical power output limitations of their muscles. Click beetles use springs and latches to bend their bodies at the thoracic hinge and then unbend extremely quickly, resulting in a clicking motion. When unconstrained, this quick clicking motion results in a jump. While the jumping motion has been studied in depth, the physical mechanisms enabling fast unbending have not. Here, we first identify and quantify the phases of the clicking motion: latching, loading, and energy release. We detail the motion kinematics and investigate the governing dynamics (forces) of the energy release. We use high-speed synchrotron X-ray imaging to observe and analyze the motion of the hinge’s internal structures of four Elater abruptus specimens. We show evidence that soft cuticle in the hinge contributes to the spring mechanism through rapid recoil. Using spectral analysis and nonlinear system identification, we determine the equation of motion and model the beetle as a nonlinear single-degree-of-freedom oscillator. Quadratic damping and snap-through buckling are identified to be the dominant damping and elastic forces, respectively, driving the angular position during the energy release phase. The methods used in this study provide experimental and analytical guidelines for the analysis of extreme motion, starting from motion observation to identifying the forces causing the movement. Here, the tools demonstrated here can be applied to other organisms to enhance our understanding of the energy storage and release strategies small animals use to achieve extreme accelerations repeatedly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Edgewise Structural Damping of a 2.8-MW Land-Based Wind Turbine Rotor Blade

Modern wind turbines push the predictive capabilities of state-of-the-art aero-servo-elastic tools. The existing limitations hide across the numerical tool chain and can result in serious issues, such as missing aeroelastic instabilities during the design phase. Structural damping is an input that is usually hard to estimate, but also has a major impact on the turbine behavior. In this paper, we discuss an experiment that aims to accurately quantify the structural damping characterizing the edgewise modes of modern wind turbine blades. The experiment is carried out on a 2.8-MW land-based wind turbine and features a fast yaw actuation that induces an edgewise motion on one of the three blades. The Covariant-subspace system identification (Cov-SSI) method is then used to post-process the blade root moment to estimate the short-term edgewise structural damping. Despite limitations of the Cov-SSI method, which consistently under-predicts the absolute values of damping, we observe that structural damping decreases across the first three blade edgewise modes, which is different from the stiffness-proportional damping model that assumes that structural damping increases with the modes. This paper argues that a stiffness-proportional damping model, which is implemented in most aeroelastic tools, is therefore not conservative and might hide aeroelastic instabilities that can instead appear in the field.

17 WIND ENERGY↗
DOE OSTI2020

AI-optimized detector design for the future Electron-Ion Collider: the dual-radiator RICH case

Advanced detector R&D requires performing computationally intensive and detailed simulations as part of the detector-design optimization process. Here, we propose a general approach to this process based on Bayesian optimization and machine learning that encodes detector requirements. As a case study, we focus on the design of the dual-radiator Ring Imaging Cherenkov (dRICH) detector under development as a potential component of the particle-identification system at the future Electron-Ion Collider (EIC). The EIC is a US-led frontier accelerator project for nuclear physics, which has been proposed to further explore the structure and interactions of nuclear matter at the scale of sea quarks and gluons. We show that the detector design obtained with our automated and highly parallelized framework outperforms the baseline dRICH design within the assumptions of the current model. Our technique can be applied to any detector R&D, provided that realistic simulations are available.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Energy-Optimal Vehicle Longitudinal Motion Control via Pontryagin’s Minimum Principle and Ultra-Local Model

Longitudinal vehicle motion control is essential for enhancing performance and optimizing a vehicle’s energy usage. However, it remains a challenging task due to the nonlinear and uncertain nature of vehicle dynamics, along with varying driving conditions. This paper presents a novel ultra-local optimal control approach based on Pontryagin’s Minimum Principle (PMP) that circumvents the need for detailed system identification by employing an ultra-local model. The control objective is to minimize the total energy consumption under boundary conditions while ensuring smooth traction force generation. The proposed approach is evaluated using a high-fidelity vehicle model in three representative scenarios: (i) nominal driving, (ii) a change in tire road friction coefficient (TRFC) from 0.5 to 0.65 and road slope from 0% to 5% during the maneuver, with target velocity unchanged, and (iii) a change in target velocity from 20 m/s to 0 m/s during the maneuver, while maintaining nominal TRFC and slope conditions. The simulation results demonstrate that the proposed method delivers robust performance, effectively balancing consumption and tracking accuracy in all tested scenarios.

Waleed khan, Muhammad [The University of Texas at ↗
DOE OSTI2024

Hybrid Modeling of Three-Phase Grid-Supporting Inverters for Dynamic Studies

Grid technologies connected by power electronic converter (PEC) interfaces continually implement grid support functions mandated by grid codes and standards. The transition to converter-based generation demands precise PEC models to assess system dynamics, which have been previously overlooked in conventional power systems. This study proposes a hybrid method for analyzing grid-connected three-phase PEC dynamics with the IEEE standard 1547-2018 Volt-VAr mode that combines physics and data-driven techniques. The physics model reflects the PEC’s internal behavior, whereas the data-driven modeling technique evaluates the grid-supporting capabilities of the smart PEC. The system identification approach is used to generate dynamic PEC models based on changing grid voltage and measured current injected into the grid by the PEC. In the Volt-VAr support mode, a detailed topological model including switches is utilized to compare the goodness-of-fit of the extracted hybrid dynamic model. The results demonstrate that the hybrid PEC model in the Volt-VAr mode accurately matches the dynamics with the topological model.

Subedi, Sunil↗
DOE OSTI2019

Feedback Resonating Control for a Wave Energy Converter

Through the use of advanced control techniques, wave energy converters (WECs) can achieve substantial increases in energy absorption. The motion of the WEC device is a significant contribution to the energy absorbed by the device. Reactive (complex conjugate) control maximizes the energy absorption due to the impedance matching. The issue with complex conjugate control is that, in general, the controller is noncausal, which requires prediction of the incoming waves. This article explores the potential of employing system identification techniques to build a causal transfer function that approximates the complex conjugate controller over a finite frequency band of interest. This approach is quite viable given the band-limited nature of ocean waves. The resulting controller is stable, and the average efficiency of the power captured by the causal controller in realistic ocean waves is 99%, when compared to the noncausal complex conjugate.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Reducing Urban Traffic Congestion Using Deep Learning and Model Predictive Control

This article proposes a deep learning (DL)-based control algorithm—DL velocity-based model predictive control (VMPC)—for reducing traffic congestion with slowly time-varying traffic signal controls. This control algorithm consists of system identification using DL and traffic signal control using VMPC. For the training process of DL, we established a modeling error entropy loss as the criteria inspired by the theory of stochastic distribution control (SDC) originated by the fourth author. Herein, simulation results show that the proposed algorithm can reduce traffic congestion with a slowly varying traffic signal control input. Results of an ablation study demonstrate that this algorithm compares favorably to other model-based controllers in terms of prediction error, signal varying speed, and control effectiveness.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

DQ Admittance Model Extraction for IBRs via Gaussian Pulse Excitation

While $dq$ admittance models have shown to be very useful for stability analysis, extracting admittance models of inverter-based resources (IBRs) from the electromagnetic transient (EMT) simulation environment using frequency scans takes time. In this letter, a new perturbation method based on Gaussian pulses in combination with the system identification algorithms shows great promise for parametric $dq$ admittance model extraction. We present the $dq$ admittance model extracting method for a type-4 wind turbine. Challenges in implementing Gaussian pulse excitation are also pointed out. In conclusion, the extracted $dq$ admittance model via the new method shows to have a high matching degree with the measurements obtained from frequency scans.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Control-Oriented Modeling of Cycle-to-Cycle Combustion Variability at the Misfire Limit in SI Engines

A control-oriented model is presented that can capture the prior-cycle correlation of combustion cycles during conditions with high levels of exhaust gas recirculation (EGR). Combustion events are modeled in discrete time and the dynamic evolution is captured by the residual air, fuel, and inert gas trapped in the combustion chamber. The mathematical formulation of the model is presented together with the calibration procedure to emulate a particular engine operating condition. A cycle-to-cycle system identification methodology is described which allows regressing model parameters from experimental data. Simulations are presented and compared to real engine measurements to show the modeling potential for analysis and control of combustion events.

Maldonado Puente, Bryan↗
DOE OSTI2015

SU-E-I-74: Image-Matching Technique of Computed Tomography Images for Personal Identification: A Preliminary Study Using Anthropomorphic Chest Phantoms

Purpose: Fingerprints, dental impressions, and DNA are used to identify unidentified bodies in forensic medicine. Cranial Computed tomography (CT) images and/or dental radiographs are also used for identification. Radiological identification is important, particularly in the absence of comparative fingerprints, dental impressions, and DNA samples. The development of an automated radiological identification system for unidentified bodies is desirable. We investigated the potential usefulness of bone structure for matching chest CT images. Methods: CT images of three anthropomorphic chest phantoms were obtained on different days in various settings. One of the phantoms was assumed to be an unidentified body. The bone image and the bone image with soft tissue (BST image) were extracted from the CT images. To examine the usefulness of the bone image and/or the BST image, the similarities between the two-dimensional (2D) or threedimensional (3D) images of the same and different phantoms were evaluated in terms of the normalized cross-correlation value (NCC). Results: For the 2D and 3D BST images, the NCCs obtained from the same phantom assumed to be an unidentified body (2D, 0.99; 3D, 0.93) were higher than those for the different phantoms (2D, 0.95 and 0.91; 3D, 0.89 and 0.80). The NCCs for the same phantom (2D, 0.95; 3D, 0.88) were greater compared to those of the different phantoms (2D, 0.61 and 0.25; 3D, 0.23 and 0.10) for the bone image. The difference in the NCCs between the same and different phantoms tended to be larger for the bone images than for the BST images. These findings suggest that the image-matching technique is more useful when utilizing the bone image than when utilizing the BST image to identify different people. Conclusion: This preliminary study indicated that evaluating the similarity of bone structure in 2D and 3D images is potentially useful for identifying of an unidentified body.

60 APPLIED LIFE SCIENCES↗