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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 1,045 records · Page 58

Flexible Intelligent Real-time dc-ac grid Emulator (FIRE): Power Electronic Hardware-in-the-Loop (PE-HIL) Amplifier

Grid modernization efforts are leading to increased penetration of power electronics in the existing alternating current (ac) bulk power systems (BPS). Some examples of power electronics based applications that are being developed in BPS include high-voltage direct current (HVdc) systems, renewable generation systems, energy storage systems, and others. One of the requirements to succeed in the goals of grid modernization (like increased efficiency and reliability) is to setup a platform that can evaluate basic building blocks of such systems. For example, the basic building block of a modular multilevel converter (MMC)-based HVdc system is a submodule (SM). The evaluation platform will provide means to innovate new SM circuit architectures, new semiconductor devices in the SM, new gate-drivers, new controllers, and others. The flexible intelligent real-time dc-ac grid emulator (FIRE) platform incorporates the evaluation capability to evaluate the basic building blocks. The FIRE platform incorporates this evaluation capability through the power electronic hardware-in-the-loop (PE-HIL) concept. The PE-HIL for MMC-HVdc system can evaluate SMs in the MMC. In this paper, the design of amplifier required to perform PE-HIL simulation is presented. Experimental results of the amplifier and the simulation results of the PE-HIL concept utilizing the amplifier are presented.

Debnath, Suman↗

Diagonal Shadows Could Cause Arcs in Thin-Film Modules With P4 Scribes

Thin-film photovoltaic (PV) modules are often made using monolithic integration (MLI), regardless of absorber technology. MLI modules sometimes use a fourth pattern of scribe lines, P4, to divide modules into parallel substrings of cells. We simulated diagonal shadows in such modules and show that they cause a voltage difference across P4. This voltage can be enough to cause an arc across P4. An arc inside a PV module can cause burned polymers and broken glass. Such packaging failures create a risk of fire or electric shock in any PV module. These hazards go beyond the permanent loss of efficiency that vertical shadows can cause. Here, we propose several solutions to this potential problem.

14 SOLAR ENERGY↗

w22_laser_radiography - Laser-Based MeV Radiography

This project seeks to develop novel x-ray sources based on high-power short-pulse lasers with unique advantages, including small spot size, flexible configuration, and tailorable spectra. Kinetic plasma simulations using the VPIC particle in cell code will be performed to support the R&D goals of this project. If successful, this effort will allow LANL to deploy flexible, compact x-ray sources for static tomographic radiography and dynamic multi-axis radiography at our firing sites and facilities such as pRad and U1a. The higher resolution, shorter pulse duration, and tunability of our proposed sources will enable new applications in the weapons program and broader scientific community. This effort advances the LANL FY22 Strategic Investment Plan priority of “[r]adiographic tools for dynamic and static imaging with improved spatial and temporal resolution, sensitivity, and dose.”

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A simple lightning parameterization for calculating global lightning distributions

A simple parameterization has been developed to simulate global lightning distributions. Convective cloud top height is used as the variable in the parameterization, with different formulations for continental and marine thunderstorms. The parameterization has been validated using two lightning data sets: one global and one regional. In both cases the simulated lightning distributions and frequencies are in very good agreement with the observed lightning data. This parameterization could be used for global studies of lightning climatology; the earth's electric circuit; in general circulation models for modeling global lightning activity, atmospheric NO(x) concentrations, and perhaps forest fire distributions for both the present and future climate; and, possibly, even as a short-term forecasting aid.

Price, Colin↗

Optimal Space Station solar array gimbal angle determination via radial basis function neural networks

The potential for excessive plume impingement loads on Space Station Freedom solar arrays, caused by jet firings from an approaching Space Shuttle, is addressed. An artificial neural network is designed to determine commanded solar array beta gimbal angle for minimum plume loads. The commanded angle would be determined dynamically. The network design proposed involves radial basis functions as activation functions. Design, development, and simulation of this network design are discussed.

Clancy, Daniel J.↗

STS-96 Press Briefing and MODE-1 Egress Training for TCDT

Live footage shows the members of the STS-96 crew, Commander Kent V. Rominger, Pilot Rick D. Husband, and Mission Specialists Ellen Ochoa, Tamara E. Jernigan, Daniel T. Barry, Julie Payette and Valery Ivanovich Tokarev participating in a Press Conference and Egress Training for a Terminal Countdown Demonstration Test. Scenes of Capt. Steve Kelly, Fire Services, explaining the emergency egress procedure to the STS-96 crew is presented. Mission Specialist Tokarev is shown releasing a slide-wire basket. Mission Specialist Barry is also seen in the evacuation seat with the Training Officer Gina Tucker behind him. The TCDT activities include simulated countdown exercises and inspection of the mission payloads in the orbiter's payload bay.

Source record↗

Electrical and Dielectric Characterizations of HTCC Electronic Packages for High Temperature Harsh Environment Applications

A prototype high temperature co-fired ceramic (HTCC) alumina packaging system composed of a 32-I/Os package and a compatible circuit board was previously developed and demonstrated for long term operation in 500 °C environments. The electrical / dielectric parasitic parameters of that chip level package were characterized and reported. This co-fired packaging system with platinum (Pt) conductor has successfully facilitated tests of silicon carbide (SiC) analog and digital integrated circuits (ICs) developed at NASA GRC at 500°C for up to 10,000 hours in ambient oven environment and 60 earth days in Venus surface environment with simulated temperature, pressure, and chemical constituents. Based on these previous results, this paper introduces new designs of Pt-HTCC packages with 16, 24, and 44 I/Os for packaging a new generation SiC ICs with 8, 24, 56, 62, and 72 I/Os to be tested in high temperature harsh environments. The package with 44 I/Os is specifically designed for the new SiC ICs with 56, 62, and 72-I/Os and electrical connection needs, the power pads of this package are consolidated, and an array of I/O pads distributed on separated vertical levels (inside the package) is used to control the overall package dimensions and mitigate the parasitic effects at high temperatures. This paper will present the detailed design of these chip-level packages and results of electrical and dielectric characterization of these newly fabricated chip-level Pt-HTCC packages.

High temperature↗

Electrical and Dielectric Characterizations of HTCC Electronic Packages for High Temperature Harsh Environment Applications

A prototype high temperature co-fired ceramic (HTCC) alumina packaging system composed of a 32-I/Os package and a compatible circuit board was previously developed and demonstrated for long term operation in 500 °C environments. The electrical / dielectric parasitic parameters of that chip level package were characterized and reported. This co-fired packaging system with platinum (Pt) conductor has successfully facilitated tests of silicon carbide (SiC) analog and digital integrated circuits (ICs) developed at NASA GRC at 500°C for up to 10,000 hours in ambient oven environment and 60 earth days in Venus surface environment with simulated temperature, pressure, and chemical constituents. Based on these previous results, this paper introduces new designs of Pt-HTCC packages with 16, 24, and 44 I/Os for packaging a new generation SiC ICs with 8, 24, 56, 62, and 72 I/Os to be tested in high temperature harsh environments. The package with 44 I/Os is specifically designed for the new SiC ICs with 56, 62, and 72-I/Os and electrical connection needs, the power pads of this package are consolidated, and an array of I/O pads distributed on separated vertical levels (inside the package) is used to control the overall package dimensions and mitigate the parasitic effects at high temperatures. This paper will present the detailed design of these chip-level packages and results of electrical and dielectric characterization of these newly fabricated chip-level Pt-HTCC packages.

High temperature↗

Using FENOSOL{sup TM} Phenolic Foam as a Shock Absorber for Type B Packaging - 17256

Type B and fissile material transportation packages are designed to withstand deformation from dynamic forces experienced during impacts in hypothetical accident conditions. A critical aspect is to ensure the containment system is not breached. The package design normally includes impact limiters made up of a shell filled with energy-absorbing material. Various types of materials are used as energy absorbers, including wood, foam, and honeycomb structures. Synthetic foam is an ideal material for impact limiters; it has isotropic material properties, it acts as a heat insulator during fire conditions, and it maintains structural integrity at high temperatures. In addition, the density of the foam may be controlled during the manufacturing process, allowing the cask designer flexibility to select the right density for each application. The foam properties can be used as inputs for numerical simulations of dynamic impacts. These simulations are a key component of the safety analysis report for Type B transportation casks. Robatel has recently invested in equipment to produce FENOSOL{sup TM} phenolic foam in our factory for use in our cask designs. This acquisition was made jointly between Robatel and the CEA, with Robatel ensuring the industrialization of the product. In the past decade, this foam was successfully integrated into more than 10 European cask designs, and there has been extensive in-laboratory characterization of its properties. FENOSOL{sup TM} has already been accepted by the French Nuclear Safety Authority (ASN) as a shock absorbing material for use in cask designs. Since the acquisition of the phenolic foam production process by Robatel, a new research and development program has been launched to provide more accurate information to our clients, extend the range of application of this foam, and to improve its properties. Robatel has built an extensive database of material characteristics through the use of a universal mechanical tester, a scanning electron microscope, and a nuclear magnetic resonance spectrometer. In addition, Robatel has successfully implemented FENOSOL{sup TM} in two recent cask designs. This included scale model drop testing of a 9 meter drop in three orientations, and a pin puncture drop test. Robatel is in the process of producing FENOSOL{sup TM} samples for testing according to ASTM standards. Various densities will be included in the study. The testing will include duro-meter hardness, specific heat, thermal conductivity, compressive strength and modulus, and tensile strength. Once the testing is complete, Robatel will compile the data in the form of product specification sheets for each density. These information sheets and test reports will be used to validate FENOSOL{sup TM} for use in future impact limiters for the North American Type B cask market. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

The key role of forest disturbance in reconciling estimates of the northern carbon sink

Northern forests are an important carbon sink, but our understanding of the driving factors is limited due to discrepancies between dynamic global vegetation models (DGVMs) and atmospheric inversions. We show that DGVMs simulate a 50% lower sink (1.1 ± 0.5 PgC yr –1 over 2001–2021) across North America, Europe, Russia, and China compared to atmospheric inversions (2.2 ± 0.6 PgC yr –1 ). We explain why DGVMs underestimate the carbon sink by considering how they represent disturbance processes, specifically the overestimation of fire emissions, and the lack of robust forest demography resulting in lower forest regrowth rates than observed. We reconcile net sink estimates by using alternative disturbance-related fluxes. We estimate carbon uptake through forest regrowth by combining satellite-derived forest age and biomass maps. We calculate a regrowth flux of 1.1 ± 0.1 PgC yr –1 , and combine this with satellite-derived estimates of fire emissions (0.4 ± 0.1 PgC yr –1 ), land-use change emissions from bookkeeping models (0.9 ± 0.2 PgC yr –1 ), and the DGVM-estimated sink from CO 2 fertilisation, nitrogen deposition, and climate change (2.2 ± 0.9 PgC yr –1 ). The resulting ‘bottom-up’ net flux of 2.1 ± 0.9 PgC yr –1 agrees with atmospheric inversions. The reconciliation holds at regional scales, increasing confidence in our results.

54 ENVIRONMENTAL SCIENCES↗

NSRD-06. Computational Capability to Substantiate DOE-HDBK-3010 Data

Safety basis analysts throughout the U.S. Department of Energy (DOE) complex rely heavily on the information provided in the DOE Hand book, DOE-HDBK-3010, Airborne Release Fractions/Rates and Resp irable Fractions for Nonreactor Nuclear Facilities , to determine source terms. In calcula ting source terms, analysts tend to use the DOE Handbook's bounding values on airbor ne release fractions (ARFs) and respirable fractions (RFs) for various cat egories of insults (representing potential accident release categories). This is typica lly due to both time constraints and the avoidance of regulatory critique. Unfort unately, these bounding ARFs/RFs represent extremely conservative values. Moreover, th ey were derived from very limited small- scale table-top and bench/labo ratory experiments and/or fr om engineered judgment. Thus the basis for the data may not be re presentative to the actual unique accident conditions and configura tions being evaluated. The goal of this res earch is to develop a more ac curate method to identify bounding values for the DOE Handbook using the st ate-of-art multi-physics-based high performance computer codes. This enable s us to better understand the fundamental physics and phenomena associated with the ty pes of accidents for the data described in it. This research has examined two of the DOE Handbook's liquid fire experiments to substantiate the airborne release frac tion data. We found th at additional physical phenomena (i.e., resuspension) need to be included to derive bounding values. For the specific cases of solid powder under pre ssurized condition and mechanical insult conditions the codes demonstrated that we can simulate the phenomena. This work thus provides a low-cost method to establis h physics-justified sa fety bounds by taking into account specific geometri es and conditions that may not have been previously measured and/or are too costly to do so.

97 MATHEMATICS AND COMPUTING↗

Initial Atmospheric Transport of Particles

A new version of the Initial Atmospheric Transport (IAT) model has been developed. This report fully characterizes the new model. IAT is designed to model heat release into the atmosphere that contains contaminated particles. The heat release forms a buoyant puff or plume. Buoyancy is quickly dissipated in 10's to 100's of seconds through drag and entrainment of ambient air. The final location of contaminant particles in the atmosphere after dissipation of abnormal heat is an important input to long term transportation codes such as the National Oceanic and Atmospheric Administration's (NOAA) Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) code. Ultimately the settling of contaminants after long term transport provides a basis for estimating health consequences. In comparison to the old version, the new model includes explicit simulation of particles, newly formulated equations of motion for a rising puff, and a new plume model. The plume model releases many instances of a single puff along a single trajectory in a way that balances energy released over a longer period than would be appropriate for a single puff. The puff model has additions for vorticity, turbulence, virtual mass, drag, and entrainment. The particle model leads to direct interfacing between IAT and the long-term transport code HYSPLIT. Previously, particle locations were given a pattern based on IAT's puff trajectory with no particle simulation. Now, particles are explicitly simulated, and 3-D spatial distributions of particles are output based on final positions. Ballistic particles are thrown outward at high velocity from explosive events and tend to hit the ground before the end of the simulation. Non-ballistic particles tend to get pulled into the rising puff s ring of vorticity with some escaping to ambient conditions as buoyant energy dissipates. A new model verification and validation effort was made for the new plume model. The Wallops Island Solid Rocket Propellant (SRP) fire plume was extracted to a 3-D transient dataset. After calibration, the model performs better than previous single puff attempts. Even so, error levels in the process used to estimate location and ambient weather conditions approach 30%. This leads to the conclusion that unplanned photogrammetry evaluations of the IAT model are useful but not sufficiently accurate to quantify model parameters. Like previous attempts, the vertical motion entrainment parameters come out much too high in comparison to values for other studies in the literature. It is suspected that a new model of shear entrainment would alleviate this problem. Unfortunately, IAT already has more calibration parameters than the data comparisons thus far can resolve with statistical certainty. This underscores the need to verify and validate the IAT model using detailed CFD studies that allow ideal statistical comparison with the IAT model for hundreds of cases. Even so, validation by comparison to carefully planned experiments (i.e. with acceptable error levels) is also necessary because the dynamics of entrainment are at a sub-grid level for CFD. Though better validation and verification are most important, many new enhancements are still envisioned for future IAT development. These include particle rain out due to condensation and agglomeration of water, direct connection to the North American Mesoscale (NAM) weather dataset, dynamic weather conditions, including ambient particle entrainment into the puff, and detrainment at the puff to ambient mixing interface. In general, including detailed aerosol dynamics is the greatest coming challenge which will require an entire new sub-model in IAT. This is very important if contaminant particles change in such a way that they increase or decrease in their potential harm to the environment.

54 ENVIRONMENTAL SCIENCES↗

Measurements and Prediction of Ash Deposition in a Cyclone-Fired Boiler Operating under Variable Load Conditions

Measurements of ash deposition rates were made between the secondary superheater and reheater sections of a 450 MW cyclone-fired lignite boiler as the operational load varied from 33 to 100%. Significant reductions in deposition rates with a decrease in operational load were observed. To uncover the causative mechanisms behind these observations, operational data from the power plant were used to carry out computational fluid dynamic (CFD) simulations of the boiler. After ascertaining that the gas temperatures and velocities at various sections within the boiler were being represented adequately, decoupled simulations of the ash deposition process on the deposit probe were carried out using a finely resolved boundary layer mesh. Fly ash particle size distribution (PSD) and its concentration for the decoupled calculations were determined from stand-alone cyclone barrel simulations. The ash partitioning (mass %) between the fly ash and slag was found to be ~50:50, which was in line with previous field observations, and it did not vary significantly across different cyclone loads. The predicted PSD of the deposit ash was concentrated in the size range 10–30 microns, which was in agreement with cross-sectional images of the deposit obtained from the measurements. At lower loads, sharp variations in the deposition rates were predicted in the gas temperature range 950–1150 K. The particle kinetic energy—particle viscosity-based capture methodology utilized in this study in conjunction with appropriate ash compositions, ash viscosity models and gas temperature estimates can help estimate slagging propensities at different loads reasonably well in these systems.

Krishnamoorthy, Gautham (ORCID:0000000255205092)↗

Satellite-based evaluation of AeroCom model bias in biomass burning regions

Global models are widely used to simulate biomass burning aerosol (BBA). Exhaustive evaluations on model representation of aerosol distributions and properties are fundamental to assess health and climate impacts of BBA. Here we conducted a comprehensive comparison of Aerosol Comparisons between Observations and Models (AeroCom) project model simulations with satellite observations. A total of 59 runs by 18 models from three AeroCom Phase-III experiments (i.e., biomass burning emissions, CTRL16, and CTRL19) and 14 satellite products of aerosols were used in the study. Aerosol optical depth (AOD) at 550 nm was investigated during the fire season over three key fire regions reflecting different fire dynamics (i.e., deforestation-dominated Amazon, Southern Hemisphere Africa where savannas are the key source of emissions, and boreal forest burning in boreal North America). The 14 satellite products were first evaluated against AErosol RObotic NETwork (AERONET) observations, with large uncertainties found. But these uncertainties had small impacts on the model evaluation that was dominated by modeling bias. Through a comparison with Polarization and Directionality of the Earth’s Reflectances measurements with the Generalized Retrieval of Aerosol and Surface Properties algorithm (POLDER-GRASP), we found that the modeled AOD values were biased by –93 % to 152 %, with most models showing significant underestimations even for the state-of-the-art aerosol modeling techniques (i.e., CTRL19). By scaling up BBA emissions, the negative biases in modeled AOD were significantly mitigated, although it yielded only negligible improvements in the correlation between models and observations, and the spatial and temporal variations in AOD biases did not change much. For models in CTRL16 and CTRL19, the large diversity in modeled AOD was in almost equal measures caused by diversity in emissions, lifetime, and the mass extinction coefficient (MEC). We found that in the AeroCom ensemble, BBA lifetime correlated significantly with particle deposition (as expected) and in turn correlated strongly with precipitation. Additional analysis based on Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) aerosol profiles suggested that the altitude of the aerosol layer in the current models was generally too low, which also contributed to the bias in modeled lifetime. Modeled MECs exhibited significant correlations with the Ångström exponent (AE, an indicator of particle size). Comparisons with the POLDER-GRASP-observed AE suggested that the models tended to overestimate the AE (underestimated particle size), indicating a possible underestimation of MECs in models. The hygroscopic growth in most models generally agreed with observations and might not explain the overall underestimation of modeled AOD. Our results imply that current global models contain biases in important aerosol processes for BBA (e.g., emissions, removal, and optical properties) that remain to be addressed in future research.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Remote Sensing of Liquid Water and Ice Cloud Optical Thickness and Effective Radius in the Arctic: Application of Airborne Multispectral MAS Data

A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of clouds, sea ice, snow, and tundra surfaces at 50 discrete wavelengths between 0.47 and 14.0 microns. These observations were obtained from the NASA ER-2 aircraft as part of the FIRE Arctic Clouds Experiment, conducted over a 1600 x 500 km region of the north slope of Alaska and surrounding Beaufort and Chukchi Seas between 18 May and 6 June 1998. Multispectral images of the reflection function and brightness temperature in 11 distinct bands of the MODIS Airborne Simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, and heavy aerosol over five different ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both water and ice clouds that were detected during one flight line on 4 June. This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS data in Alaska, is quite capable of distinguishing clouds from bright sea ice surfaces during daytime conditions in the high Arctic. Results of individual tests, however, make it difficult to distinguish ice clouds over snow and sea ice surfaces, so additional tests were added to enhance the confidence in the thermodynamic phase of clouds over the Beaufort Sea. The cloud optical thickness and effective radius retrievals used 3 distinct bands of the MAS, with the newly developed 1.62 and 2.13 micron bands being used quite successfully over snow and sea ice surfaces. These results are contrasted with a MODIS-based algorithm that relies on spectral reflectance at 0.87 and 2.13 micron.

King, Michael D.↗

Exploring the Inorganic Composition of the Asian Tropopause Aerosol Layer Using Medium-Duration Balloon Flights

Satellite observations have revealed an enhanced aerosol layer near the tropopause over Asia during the summer monsoon, called the “Asian Tropopause Aerosol Layer” (ATAL). In this work, aerosol particles in the ATAL were collected with a balloon-borne impactor near the tropopause region over India, using extended-duration balloon flights, in summer 2017 and winter 2018. The chemical composition of these particles was further investigated by quantitative analysis using offline ion chromatography. Nitrate (NO_3 ^1) and nitrite (NO_2 ^-) were found to be the dominant ions in the collected aerosols with values ranging between 87 and 343 ng m^(−3) at STP (standard temperature and pressure) during the summer campaign. In contrast, sulfate (SO_4 ^(2-)) levels were found to be above the detection limit (>10 ng m^(−3) at STP) only in winter. In addition, we determined the origin of the air masses sampled during the flights using the analysis of back trajectories as well as a convective proxy from cloud-top temperature fields derived from a geostationary satellite. The results obtained from this analysis were put into the context of large-scale transport and aerosol distribution using GEOS-Chem chemical transport model simulations. The first flight in summer 2017 which sampled an air mass within the Asian monsoon anticyclone (AMA), influenced by convection over Western China, was associated with particle size diameters from 0.05 to 0.15 µm. In contrast, the second flight sampled air masses at the edge of the AMA associated with a larger particle size radius (>2 µm) with a higher NO_2 ^- concentration. The sampled air masses in winter 2018 were likely affected by smoke from the Pacific Northwest fire event in Canada, which occurred 7 months before our campaign, associated with concentration enhancements of SO_4 (^2-) and Ca^(2+). Overall, our results suggest that nitrogen-containing particles represent a large fraction of cloud-free and in-cloud aerosols populating the ATAL, which is partially in agreement with the results from aircraft measurements during the StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) campaign. The exact nature of those particles is still unknown, but their coincidences with subvisible cirrus clouds and their sizes suggest nitric acid trihydrate (NAT) as a possible candidate, as NAT has already been observed in the tropical upper troposphere and lower stratosphere in other studies. Furthermore, GEOS-Chem model simulations indicate that lightning NOx emissions could have significantly impacted the production of nitrate aerosols sampled during the summer of 2017.

Hazel Vernier↗

Real-time optimization of multi-cell industrial evaporative cooling towers using machine learning and particle swarm optimization

Existing electrical generating stations must operate with greater flexibility due to increasing renewable energy penetration on the electrical grid, and many coal-fired power stations have transitioned away from baseload operation to load-following operation to aid in grid stability. In cases where multiple independently controlled cooling tower cells are used in parallel for the cooling purposes of such stations, there is an opportunity to increase plant efficiency through data-driven optimization across their full load ranges. This work presents a novel application of real-time optimization using machine learning and particle swarm optimization on a multi-cell induced-draft cooling tower servicing a coal-fired power station under variable load. This is the first work to demonstrate simultaneous optimization of a multi-cell cooling tower, in addition to using machine learning for closed-loop control on a cooling tower. A novel control configuration is presented that ensures original control logic is not adversely affected and that the overall plant process is not disrupted using only existing hardware and operational data. To verify this methodology, the 12 independent cooling tower cells are simulated in parallel using historic operating data to demonstrate the effectiveness of real-time optimization compared to current practice. An artificial neural network is trained to predict overall cooling tower power consumption using only operational data and ambient conditions with an R2 value of greater than 0.96. The real-time optimization using particle swarm yields 6.7% annual energy usage savings compared to current practices, although the extent of the real-time savings varies greatly with both plant load and environmental conditions. This is particularly significant for a variable load situation because frequent ramping typically results in reduced overall efficiency. Furthermore, this proposed AI-based solution presents an opportunity to improve the overall heat rate of a load-following coal-fired power plant without the need to perform extensive first-principles modeling or add additional hardware to the cooling tower, resulting in more resources conserved and less overall emissions per unit of electricity generated.

42 ENGINEERING↗