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At least 991 records · Page 55

Baltimore Social-Environmental Collaborative (BSEC) Doppler Lidar & Derived Products

This repository contains all processed Doppler‐lidar outputs from the PSU lidar deployed for the Baltimore Social‐Environmental Collaborative (BSEC) project. Vertical Stare Scans (fixed‐beam, vertical profiling): 1 Hz backscatter intensity (m⁻¹ sr⁻¹), signal‐to‐noise ratio (unitless), and Doppler vertical‐velocity (m s⁻¹) on 30 m range gates (and 3 m range gates), stored as CF-compliant NetCDF. Wind Profiles (horizontal‐wind retrieval): daily NetCDF outputs of retrieved horizontal wind speed (m s⁻¹) and direction (degrees), computed from the angled‐scan returns. Profile Statistics (summary statistics on the vertical velocity): 15 min windows (default) of mean, variance, skewness, kurtosis, high-frequency variance, etc., as a function of height; saved as CF-compliant NetCDF files. Boundary Layer Height (BLH) (fuzzy-logic output): 15 min BLH estimates (m), with lower/upper fuzzy bounds (m) and a quality flag (0–4) indicating data status (e.g., no data, good, ran out of signal, below range, cloud-topped). Cloud Base Height (Haar-gradient detection): 10 min estimates of cloud-base height (m). All five product streams are organized by year and date under their own top-level folders (01_Vertical_Stare_Scans/ through 05_Cloud_Height/). Each folder contains a data_ /YYYY/ subdirectory with daily CF-compliant NetCDF outputs (96 windows per day at 15 min intervals). Global attributes in each file include creation history, version (3.0.1), institution, and source. Instrument & MeasurementsThe PSU Doppler Lidar samples aerosol backscatter (m⁻¹ sr⁻¹), signal-to-noise ratio, and radial velocity at ~1 Hz. Vertical stare scans point the beam straight up; after collecting angled scans through multiple elevation angles, the "Wind Profiles" product contains the fully retrieved horizontal wind speed and direction. Data were collected continuously at ~30 m range resolution (and 3 m for the year of 2025), with a typical height ceiling of ~12 km. How to Use Open any NetCDF with Python's xarray, MATLAB, or similar CF-compliant tools. Stare scans and angled-scan retrievals (Wind Profiles) are CF-compliant daily NetCDF files. Profile-Statistics, BLH, and Cloud Height files are daily 15 min (10 min for Cloud Heights) summaries (96 time steps per file). Inspect the included variables (e.g., vertical_velocity_variance, wind_speed, BLH, cloud_base_height) for your analyses. Use the quality flags (BLH_flag, cloud_flag) to filter out poor-quality retrievals. For more information or questions about processing methods, please contact:Nicholas E. Prince ⟨nec5299@psu.edu⟩Penn State Department of Meteorology & Atmospheric Science

Air Quality↗

Analysis of Power Electronic Solutions for Wide-Range Wave Energy Input

Wave energy is a largely untapped energy source with the potential to provide 290 TWh per year to the continental United States. As a new technology, wave energy converters are less efficient and reliable compared to established energy sources, leaving the vast energy of the sea largely unutilized. Wave energy is uniquely inconsistent, with large fluctuations. Paired with harsh operating environments and difficulty in repair, the power electronics designed to harvest wave energy need to be reliable, cost-effective, and able to work in a wide operating band. The literature on existing power electronics in wave energy converters and lessons learned across other industries provide a framework of topologies to simulate. WEC-Sim, an open-source hydrodynamic platform in MATLAB Simulink developed by the National Laboratory of the Rockies, was used to simulate a wide range of power electronics under a variety of wave conditions. This paper provides a comprehensive investigation into existing wave energy power electronics converters, state-of-the-art topologies that can be applied to wave energy, and novel solutions to wave conversion.

16 TIDAL AND WAVE POWER↗

Automatic Diabetic Macular Edema Detection in Fundus Images Using Publicly Available Datasets

Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy. In a large scale screening environment DME can be assessed by detecting exudates (a type of bright lesions) in fundus images. In this work, we introduce a new methodology for diagnosis of DME using a novel set of features based on colour, wavelet decomposition and automatic lesion segmentation. These features are employed to train a classifier able to automatically diagnose DME. We present a new publicly available dataset with ground-truth data containing 169 patients from various ethnic groups and levels of DME. This and other two publicly available datasets are employed to evaluate our algorithm. We are able to achieve diagnosis performance comparable to retina experts on the MESSIDOR (an independently labelled dataset with 1200 images) with cross-dataset testing. Our algorithm is robust to segmentation uncertainties, does not need ground truth at lesion level, and is very fast, generating a diagnosis on an average of 4.4 seconds per image on an 2.6 GHz platform with an unoptimised Matlab implementation.

59 BASIC BIOLOGICAL SCIENCES↗

Low Emittance Tuning Studies for SuperB

SuperB[1] is an international project for an asymmetric 2 rings collider at the B mesons cm energy to be built in the Rome area in Italy. The two rings will have very small beam sizes at the Interaction Point and very small emittances, similar to the Linear Collider Damping Rings ones. In particular, the ultra low vertical emittances, 7 pm in the LER and 4 pm in the HER, need a careful study of the misalignment errors effects on the machine performances. Studies on the closed orbit, vertical dispersion and coupling corrections have been carried out in order to specify the maximum allowed errors and to provide a procedure for emittance tuning. A new tool which combines MADX and Matlab routines has been developed, allowing for both corrections and tuning. Results of these studies are presented.

43 PARTICLE ACCELERATORS↗

Transverse Beam Emittance Measurements of a 16 MeV Linac at the Idaho Accelerator Center

A beam emittance measurement of the 16 MeV S-band High Repetition Rate Linac (HRRL) was performed at Idaho State University's Idaho Accelerator Center (IAC). The HRRL linac structure was upgraded beyond the capabilities of a typical medical linac so it can achieve a repetition rate of 1 kHz. Measurements of the HRRL transverse beam emittance are underway that will be used to optimize the production of positrons using HRRL's intense electron beam on a tungsten converter. In this paper, we describe a beam imaging system using on an OTR screen and a digital CCD camera, a MATLAB tool to extract beamsize and emittance, detailed measurement procedures, and the measured transverse emittances for an arbitrary beam energy of 15 MeV.

43 PARTICLE ACCELERATORS↗

Optimal control system design of an acid gas removal unit for an IGCC power plants with CO2 capture

Future IGCC plants with CO{sub 2} capture should be operated optimally in the face of disturbances without violating operational and environmental constraints. To achieve this goal, a systematic approach is taken in this work to design the control system of a selective, dual-stage Selexol-based acid gas removal (AGR) unit for a commercial-scale integrated gasification combined cycle (IGCC) power plant with pre-combustion CO{sub 2} capture. The control system design is performed in two stages with the objective of minimizing the auxiliary power while satisfying operational and environmental constraints in the presence of measured and unmeasured disturbances. In the first stage of the control system design, a top-down analysis is used to analyze degrees of freedom, define an operational objective, identify important disturbances and operational/environmental constraints, and select the control variables. With the degrees of freedom, the process is optimized with relation to the operational objective at nominal operation as well as under the disturbances identified. Operational and environmental constraints active at all operations are chosen as control variables. From the results of the optimization studies, self-optimizing control variables are identified for further examination. Several methods are explored in this work for the selection of these self-optimizing control variables. Modifications made to the existing methods will be discussed in this presentation. Due to the very large number of candidate sets available for control variables and due to the complexity of the underlying optimization problem, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. The second stage is a bottom-up design of the control layers used for the operation of the process. First, the regulatory control layer is designed followed by the supervisory control layer. Finally, an optimization layer is designed. In this paper, the proposed two-stage control system design approach is applied to the AGR unit for an IGCC power plant with CO{sub 2} capture. Aspen Plus Dynamics® is used to develop the dynamic AGR process model while MATLAB is used to perform the control system design and for implementation of model predictive control (MPC).

97 MATHEMATICS AND COMPUTING↗

Sensor placement algorithm development to maximize the efficiency of acid gas removal unit for integrated gasifiction combined sycle (IGCC) power plant with CO2 capture

Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In this work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. In this presentation, we will share our experience in setting up parallel computing using GA in the MATLAB® environment and present the overall approach for achieving higher computational efficiency in this framework.

97 MATHEMATICS AND COMPUTING↗

Sensor placement algorithm development to maximize the efficiency of acid gas removal unit for integrated gasification combined cycle (IGCC) power plant with CO{sub 2} capture

Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In this work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel Computing® toolbox from Mathworks®. In this presentation, we will share our experience in setting up parallel computing using GA in the MATLAB® environment and present the overall approach for achieving higher computational efficiency in this framework.

20 FOSSIL-FUELED POWER PLANTS↗

PHY and MAC Layer Design of Hybrid Spread Spectrum Based Smart Meter Network

The smart grid is a combined process of revitalizing the traditional power grid applications and introducing new applications to improve the efficiency of power generation, transmission and distribution. This can be achieved by leveraging advanced communication and networking technologies. Therefore the selection of the appropriate communication technology for different smart grid applications has been debated a lot in the recent past. After comparing different possible technologies, a recent research study has arrived at a conclusion that the 3G cellular technology is the right choice for distribution side smart grid applications like smart metering, advanced distribution automation and demand response management system. In this paper, we argue that the current 3G/4G cellular technologies are not an appropriate choice for smart grid distribution applications and propose a Hybrid Spread Spectrum (HSS) based Advanced Metering Infrastructure (AMI) as one of the alternatives to 3G/4G technologies. We present a preliminary PHY and MAC layer design of a HSS based AMI network and evaluate their performance using matlab and NS2 simulations. Also, we propose a time hierarchical scheme that can significantly reduce the volume of random access traffic generated during blackouts and the delay in power outage reporting.

Kuruganti, Phani Teja↗

Wireless Communication for Controlling Microgrids: Co-simulation and Performance Evaluation

A microgrid with wireless communication links for microgrid control has been designed and developed. The complete simulation model has been developed in MatLab SimuLink with seamless integration of the power subsystem and the communication subsystem. Unlike the conventional co-simulators that usually glue two existing simulators together by creating an interface, which has a steep learning curve, the proposed simulator is a compact single-unit model. Detailed modeling of the power subsystem and communication system is presented as well as the microgrid control architecture and strategies. The impact of different communication system performances on microgrid control has been studied and evaluated in the proposed simulator.

Mao, Rukun↗

Modeling Long-term Creep Performance for Welded Nickel-base Superalloy Structures for Power Generation Systems

We report here a constitutive model for predicting long-term creep strain evolution in’ strengthened Ni-base superalloys. Dislocation climb-bypassing’, typical in intermediate’ volume fraction (~20%) alloys, is considered as the primary deformation mechanism. Dislocation shearing’ to anti-phase boundary (APB) faults and diffusional creep are also considered for high-stress and high-temperature low-stress conditions, respectively. Additional damage mechanism is taken into account for rapid increase in tertiary creep strain. The model has been applied to Alloy 282, and calibrated in a temperature range of 1375-1450°F, and stress range of 15-45ksi. The model parameters and a MATLAB code are provided. This report is prepared by Monica Soare and Chen Shen at GE Global Research. Technical discussions with Dr. Vito Cedro are greatly appreciated. This work was supported by DOE program DE-FE0005859

Materials/Components/Instrumentation↗

Pre-Commercial Demonstration of Direct Non-Iterative State Estimator (DNSE+)

The objective of this DOE co-funded project is to demonstrate functionality and performance of a production-grade Direct Non-iterative State Estimator (DNSE) through its integration with NYPA’s Energy Management System (EMS) and an enhanced Real Time Dynamics Monitoring System (RTDMS) synchrophasor platform from Electric Power Group (EPG). A production-grade DNSE aims to overcome a major obstacle to the operational use of synchrophasor data in Synchro-Phasor Management Systems (SPMS) by providing SPMS applications with a consistent and a complete synchrophasor data foundation in the same way that a traditional EMS State Estimator (SE) provides to EMS applications. Specifically, the DNSE uses synchrophasor measurements and Supervisory Control and Data Acquisition (SCADA) measurements, together with the complete power system model, to simultaneously obtain the complete state of the entire utility’s operating model at rates that are close to the synchrophasor data rates. The full system coverage property is what distinguishes the DNSE from the linear synchrophasor SEs (which cover only parts of the operating model that are visible through synchrophasor measurements), and DNSE differs from traditional EMS SE in that the solution is obtained without iterations, without initial values (hence the “direct” in the name), and at a much higher execution rate. This presentation provides an overview of the project objectives, a brief description of the main tasks including the development work to productize and optimize DNSE from its current MATLAB code base, RTDMS enhancement for interfacing with the DNSE, factory acceptance testing, field installation, testing and demonstration, as well as the current status of the project execution.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Significance of Dynamic and Transient Analysis in the Design and Operation of Hybrid Energy Systems

Energy systems were historically designed and operated with a specific energy conversion objective, while managing loads and resources. In the recent years, the increased utilization of non-dispatchable renewable sources such as wind and solar has played a role in power quality and the reliability of power systems. In order to mitigate the risk associated with the non-dispatchable resources an integrated approach, such as Hybrid Energy Systems (HES), has to be taken, integrating the loads and resource management between the traditional thermal power plants and the non-dispatchable resources. As our electric energy becomes more diverse in its generation resources, the HES with its operational control system, its real-time view and its dynamic decisions making will become an essential part of the integrated energy systems and improve the overall grid reliability. The operational constraints of the energy sources on both the thermal power plants and the non-dispatchable resources in HES, plays a vital role in the planning and design stage. It is an established fact that the choice of energy source depends on the available natural resources and possible infrastructure. A critical component of decision-making depends on the complementary nature and controllability of the energy sources to supply the load demands with high reliability. Controllability of complex HES to achieve desired performance and flexibility is implemented via coordinated control systems while simultaneously generating electricity and other useful products such as useful heat or hydrogen. These systems are based on instrumentation, signal processing, control theory, and engineering system design. The entire HES along with the control systems are characterized by widely varying time constants. Hence, for a well-coordinated control and operation, we propose physics based modeling of the subsystems to assist in a dynamic and transient analysis. Dynamic and transient analysis in real and non-real time domain of the potential sources is capable of providing satisfactory results at the feasibility analysis stage. A simplified HES consisting of complementary energy sources is used to demonstrate the proposed approach. Suitable real time simulations to perform dynamic and transient analysis will be performed to verify results from the non-real time analysis. The role of such analyses, especially the real time dynamic and transient analysis for manual controls is elaborated. It is also discussed that faster than real time simulation will pave the future for controller rooms and hence manual control procedures. Multiple tools such as Real Time Simulator, Matlab®, Simulink®, PSCAD®, MOOSE, etc. are expected to be used for the HES analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Temperature Profile in Fuel and Tie-Tubes for Nuclear Thermal Propulsion Systems

A finite element method to calculate temperature profiles in heterogeneous geometries of tie-tube moderated LEU nuclear thermal propulsion systems and HEU designs with tie-tubes is developed and implemented in MATLAB. This new method is compared to previous methods to demonstrate shortcomings in those methods. Typical methods to analyze peak fuel centerline temperature in hexagonal geometries rely on spatial homogenization to derive an analytical expression. These methods are not applicable to cores with tie-tube elements because conduction to tie-tubes cannot be accurately modeled with the homogenized models. The fuel centerline temperature directly impacts safety and performance so it must be predicted carefully. The temperature profile in tie-tubes is also important when high temperatures are expected in the fuel because conduction to the tie-tubes may cause melting in tie-tubes, which may set maximum allowable performance. Estimations of maximum tie-tube temperature can be found from equivalent tube methods, however this method tends to be approximate and overly conservative. A finite element model of heat conduction on a unit cell can model spatial dependence and non-linear conductivity for fuel and tie-tube systems allowing for higher design fidelity of Nuclear Thermal Propulsion.

33 ADVANCED PROPULSION SYSTEMS↗

Interferometric millimeter wave and THz wave doppler radar

A mixerless high frequency interferometric Doppler radar system and methods has been invented, numerically validated and experimentally tested. A continuous wave source, phase modulator (e.g., a continuously oscillating reference mirror) and intensity detector are utilized. The intensity detector measures the intensity of the combined reflected Doppler signal and the modulated reference beam. Rigorous mathematics formulas have been developed to extract bot amplitude and phase from the measured intensity signal. Software in Matlab has been developed and used to extract such amplitude and phase information from the experimental data. Both amplitude and phase are calculated and the Doppler frequency signature of the object is determined.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An Optimization Framework for Dynamic Hybrid Energy Systems

A computational framework for the efficient analysis and optimization of dynamic hybrid energy systems (HES) is developed. A microgrid system with multiple inputs and multiple outputs (MIMO) is modeled using the Modelica language in the Dymola environment. The optimization loop is implemented in MATLAB, with the FMI Toolbox serving as the interface between the computational platforms. Two characteristic optimization problems are selected to demonstrate the methodology and gain insight into the system performance. The first is an unconstrained optimization problem that optimizes the dynamic properties of the battery, reactor and generator to minimize variability in the HES. The second problem takes operating and capital costs into consideration by imposing linear and nonlinear constraints on the design variables. The preliminary optimization results obtained in this study provide an essential step towards the development of a comprehensive framework for designing HES.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Recent Additions in the Modeling Capabilities of an Open-Source Wave Energy Converter Design Tool: Preprint

WEC-Sim is a midfidelity numerical tool for modeling wave energy conversion devices. The code uses the MATLAB SimMechanics package to solve multibody dynamics and models wave interactions using hydrodynamic coefficients derived from frequency-domain boundary-element methods. This paper presents the new modeling features introduced in the latest release of WEC-Sim. The first feature discussed conversion of the fluid memory kernel to a state-space form. This enhancement offers a substantial computational benefit after the hydrodynamic body-to-body coefficients are introduced and the number of interactions increases exponentially with each additional body. Additional features include the ability to calculate the wave-excitation forces based on the instantaneous incident wave angle, allowing the device to weathervane, as well as import a user-defined wave elevation time series. A review of the hydrodynamic theory for each feature is provided and the successful implementation is verified using test cases.

16 TIDAL AND WAVE POWER↗

PREPARATION AND TESTING OF CORROSIONAND SPALLATION-RESISTANT COATINGS

This Energy & Environmental Research Center (EERC) project is designed to determine if plating APMT®, a specific highly oxidation-resistant oxide dispersion-strengthened FeCrAl alloy made by Kanthal, onto nickel-based superalloy turbine parts is a viable method for substantially improving the lifetimes and maximum use temperatures of the parts. The method for joining the APMT plate to the superalloys is called evaporative metal bonding and involves placing a thin foil of zinc (Zn) between the plate and the superalloy, clamping them together, and heating in an atmosphere-controlled furnace. Upon heating, the Zn melts and dissolves the oxide skins of the alloys at the bond line, allowing the two alloys to diffuse into each other. The Zn then diffuses through the alloys and evaporates from their surfaces. Laboratory testing to determine the diffusion rate of Zn through the alloys has been completed. However, an analytical solution does not exist to model the diffusion of zinc through the alloys. For this reason, a finite difference algorithm using MATLAB was developed. It makes use of the hopscotch algorithm. The model allows the user to specify the dimensions of the metal parts, the Zn concentration at the bondline, the mesh size, time step, and Zn diffusivity. The experimentally measured values of diffusivity for Zn in APMT and Rene 80/CM 247LC are approximately 2.7 × 10-12 and 4 × 10-14 m2/s, respectively. While the qualitative behavior of the model appears correct, a comparison of the diffusion predictions with the experimental results from earlier in the project indicates that the expected Zn concentration is significantly higher than that measured experimentally. The difference depends on the assumed initial concentration, which is difficult to quantify exactly under experimental conditions for t = 0. In addition to the diffusion work, the coefficients of thermal expansions were determined for each of the alloys as a function of temperature. This information has been entered into a finite element model using ANSYS so that appropriate force-applying structures can be designed for use in joining structures composed of APMT and the nickel alloys. Finite element modeling has been performed to finalize the fabrication geometry for the corrosion-testing phase. The addition of another bolt increases stress uniformity away from the region where the clamping is applied. It appears that a bolt spacing of approximately 25 mm in each jig is appropriate. This will allow the fabrication of 50-mm-wide sections of joints for the corrosion-testing task. Gasifier sampling activities continue to determine what types of trace contaminants may occur in cleaned syngas that could lead to corrosion or deposition in turbines firing coal syngas. The EERC has several pilot-scale gasifiers that are continually used in a variety of test configurations as determined by the needs of the projects that are funding the tests. We are sampling both noncombusted and combusted syngas produced during some of the pilot-scale gasifier tests. This year sampling was performed of both syngas and combusted syngas while the entrained-flow gasifier (EFG) was firing subbituminous coal from the Antelope Mine in Wyoming. Results of scanning electron microscope analyses of the syngas before combustion showed no submicron particles, only flakes of iron oxide that had likely formed on steel surfaces inside the combustor. As shown in the 2013 annual report, soot was also collected from the syngas when the much-lower-temperature fluid-bed gasifier (FBG) was fired, indicating that the much higher temperature of the EFG prevented soot formation. However, particles collected from the combusted syngas consist almost entirely of submicron soot, and little to no vaporized metals made it past the warm-gas filters and scrubbers in the high-temperature EFG system which could then deposit in a turbine system burning a higher hydrogen syngas. These results are consistent with the analyses of the particulates collected from combusted syngas when the lowertemperature FBG system is used.

Electric↗